MLOps Jobs in India.
All active MLOps roles based in India.
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Teamwork makes the stream work.
Roku is changing how the world watches TV
Roku is the #1 TV streaming platform in the U.S., Canada, and Mexico, and we've set our sights on powering every television in the world. Roku pioneered streaming to the TV. Our mission is to be the TV streaming platform that connects the entire TV ecosystem. We connect consumers to the content they love, enable content publishers to build and monetize large audiences, and provide advertisers unique capabilities to engage consumers.
From your first day at Roku, you'll make a valuable - and valued - contribution. We're a fast-growing public company where no one is a bystander. We offer you the opportunity to delight millions of TV streamers around the world while gaining meaningful experience across a variety of disciplines.
About the team
Roku pioneered streaming to the TV and continues to innovate and lead the industry. While we are well-positioned to help shape the future of television – including TV advertising – around the world, continued success relies on its investment in our machine learning capabilities. Roku offers millions of options to our users: movies, episodes, news, sports, and channels from all around the world. The Roku Content Platform is key to onboarding content into the Roku ecosystem, delighting our customers. Building a content knowledge platform that provides insights to downstream systems like Search, Recommendations, Ads, and Voice to shape customers' experiences is why we’re actively looking for a Senior Machine Learning / AI Engineer, Content Platform who can drive further innovation.
About the role
Roku pioneered streaming to the TV and continues to innovate and lead the industry. While we are well-positioned to help shape the future of television – including TV advertising – around the world, continued success relies on its investment in our machine learning capabilities.
Roku offers millions of options to our users: movies, shows, news, sports, and channels from all around the world. The Roku Content Platform is key to onboarding content into the Roku ecosystem, delighting our customers. Building a content knowledge platform that provides insights to downstream systems like Search, Recommendations, Ads, and Voice to shape customers' experiences is why we’re actively looking for a Senior Machine Learning / AI Engineering Manager who can drive further innovation.
The person in this role will leverage their technical skills, business intuition, and analytical thinking to build best-in-class machine learning products. This includes integrating Generative AI capabilities and Vision Models to enrich content quality and user engagement. This is a role for a hardened ML practitioner and a highly skilled organizational leader. You will be the architectural and operational bridge between deep AI research and fast-paced product delivery. If you know how to build a 3-year vision for content discovery and translate it into 2-week shipping cycles, this is your team.
What you’ll be doing
- Vision & Strategy: Define the roadmap for ML within the Content Platform..
- Technical Leadership: Provide high-level guidance on model architecture and MLOps infrastructure to ensure models are scalable and production-ready.
- People Management: Lead and grow a high-performing team of ML Engineers. You will be responsible for career development, performance management, and maintaining a culture of rigorous experimentation.
- Cross-Functional Execution: Partner with Product, Engineering, and Content Strategy to align ML initiatives with business goals.
- Delivery: Champion a culture of incremental delivery. Balance long-term R&D with the need to deliver measurable improvements to the production environment.
We’re excited if you have
- 10+ years of total experience in software/ML engineering, with at least 5 years in a dedicated people management leadership role.
- MS or BS in Computer Science, Mathematics, or a related quantitative field.
- You possess a deep theoretical and practical understanding of Machine Learning.
- You understand the business of streaming and how ML directly impacts the bottom line.
- You can explain complex model to a non-technical executive just as easily as you can debate architecture with a seasoned engineer.
- Proven track record of deploying large-scale ML models into production environments.
- Experience with modern ML stacks (e.g., LLMs, PyTorch, TensorFlow, Spark, and cloud-native MLOps tools).
Our Hybrid Work Approach
Roku fosters an inclusive and collaborative environment where teams work in the office Monday through Thursday. Fridays are flexible for remote work except for employees whose roles are required to be in the office five days a week or employees who are in offices with a five day in office policy.
Benefits
Roku is committed to offering a diverse range of benefits as part of our compensation package to support our employees and their families. Our comprehensive benefits include global access to mental health and financial wellness support and resources. Local benefits include statutory and voluntary benefits which may include healthcare (medical, dental, and vision), life, accident, disability, commuter, and retirement options (401(k)/pension). Employees are supported in taking time off, in accordance with local leave policies and other personal needs to support their evolving work and life needs. It's important to note that not every benefit is available in all locations or for every role. For details specific to your location, please consult with your recruiter.
Accommodations
Roku welcomes applicants of all backgrounds and provides reasonable accommodations and adjustments in accordance with applicable law. If you require reasonable accommodation at any point in the hiring process, please direct your inquiries to EmployeeRelations@Roku.com.
The Roku Culture
Roku is a great place for people who want to work in a fast-paced environment where everyone is focused on the company's success rather than their own. We try to surround ourselves with people who are great at their jobs, who are easy to work with, and who keep their egos in check. We appreciate a sense of humor. We believe a fewer number of very talented folks can do more for less cost than a larger number of less talented teams. We're independent thinkers with big ideas who act boldly, move fast and accomplish extraordinary things through collaboration and trust. In short, at Roku you'll be part of a company that's changing how the world watches TV.
We have a unique culture that we are proud of. We think of ourselves primarily as problem-solvers, which itself is a two-part idea. We come up with the solution, but the solution isn't real until it is built and delivered to the customer. That penchant for action gives us a pragmatic approach to innovation, one that has served us well since 2002.
To learn more about Roku, our global footprint, and how we've grown, visit https://www.weareroku.com/factsheet.
By providing your information, you acknowledge that you want Roku to contact you about job roles, that you have read Roku's Applicant Privacy Notice, and understand that Roku will use your information as described in that notice. If you do not wish to receive any communications from Roku regarding this role or similar roles in the future, you may unsubscribe at any time by emailing WorkforcePrivacy@Roku.com.
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About Zscaler
Zscaler accelerates digital transformation to ensure our customers can be more agile, efficient, resilient, and secure. As an AI-forward enterprise, we are constantly pushing the envelope, leveraging the world’s largest security data lake to power our cloud-native Zero Trust Exchange platform. This innovation protects our customers from cyberattacks and data loss by securely connecting users, devices, and applications in any location.
Here, impact in your role matters more than title and trust is built on results. We say, impact over activity. We seek innovators who actively use AI to amplify their impact and who thrive in an environment where we leverage intelligent systems to stay ahead of evolving threats. We believe in transparency and value constructive, honest debate—we’re focused on getting to the best ideas, faster. We build high-performing teams that can make an impact quickly and with high quality. To do this, we are building a culture of execution centered on customer obsession, collaboration, ownership, and accountability.
We value high-impact, high-accountability with a sense of urgency where you’re enabled to do your best work and embrace your potential. If you’re driven by purpose, thrive on solving complex challenges, and want to be part of the team that’s helping to secure the AI age, we invite you to bring your talents to Zscaler and help shape the future of cybersecurity.
Role
We are looking for a Staff Machine Learning Engineer to join our Exposure Management & Security Operations team. This role is a hybrid position based in Bangalore, reporting to the Sr. Manager, Engineering Strategy, Planning & Analytics. You will join the team that built the world’s largest cloud security platform from the ground up, helping to scale a multitenant architecture that serves over 15 million users globally. Your vision and passion will be critical as we continue to innovate and enable organizations to harness the speed and agility of a cloud-first strategy.
What you’ll do (Role Expectations)
- Designing and deploying scalable, reliable, and efficient production-grade Gen AI/ML systems from data ingestion to monitoring
- Driving innovation by researching and evaluating emerging AI/ML frameworks, rapidly prototyping novel solutions, and championing full-scale implementation
- Implementing and maintaining robust MLOps practices, including logging, monitoring, and CI/CD pipelines for distributed ML systems
- Leading and mentoring junior engineers in system design best practices and promoting technical excellence
- Collaborating with cross-functional teams to translate complex business needs into technical solutions
Who You Are (Success Profile)
- You thrive in ambiguity and are comfortable building the path as you walk it, seeing dynamic environments as the raw material to build something meaningful.
- You act like an owner with a passion for the mission and a bias for action, navigating seamlessly between high-level strategy and hands-on execution.
- You are a problem-solver who seeks out challenges because you are energized by finding solutions that deliver the biggest impact.
- You are a learner with a growth mindset, actively seeking feedback to become a better partner and a stronger teammate.
- You are driven by innovation and have a deep curiosity for how things work, believing in the power of technology to accelerate transformation.
What We’re Looking for (Minimum Qualifications)
- At least 5 years of experience as a Machine Learning Engineer with a track record of shipping complex, scalable ML systems to production
- Proven experience building Gen AI/ML systems with LLMs, fine-tuning, Retrieval-Augmented Generation (RAG), and Agentic AI in production environments
- Experience designing and implementing distributed ML systems with deep knowledge of MLOps, including monitoring and logging
- Strong computer science foundation in data structures, algorithms, and system design with expertise in Python and SQL
- Excellent communication and interpersonal skills to partner effectively across global engineering teams
What Will Make You Stand Out (Preferred Qualifications)
- Expertise with cloud services such as AWS, GCP, or Azure and ML platforms like Kubeflow or SageMaker
- Proficiency in systems programming languages like Go or Rust with an understanding of distributed systems and networking fundamentals
- A record of research, publications, or patents in AI/ML
#LI-Hybrid #LI-VV3
At Zscaler, we are committed to building a team that reflects the communities we serve and the customers we work with. We foster an inclusive environment that values all backgrounds and perspectives, emphasizing collaboration and belonging. Join us in our mission to make doing business seamless and secure.
Our Benefits program is one of the most important ways we support our employees. Zscaler proudly offers comprehensive and inclusive benefits to meet the diverse needs of our employees and their families throughout their life stages, including:
- Various health plans
- Time off plans for vacation and sick time
- Parental leave options
- Retirement options
- Education reimbursement
- In-office perks, and more!
Learn more about Zscaler’s Future of Work strategy, hybrid working model, and benefits here.
By applying for this role, you adhere to applicable laws, regulations, and Zscaler policies, including those related to security and privacy standards and guidelines.
Zscaler is committed to providing equal employment opportunities to all individuals. We strive to create a workplace where employees are treated with respect and have the chance to succeed. All qualified applicants will be considered for employment without regard to race, color, religion, sex (including pregnancy or related medical conditions), age, national origin, sexual orientation, gender identity or expression, genetic information, disability status, protected veteran status, or any other characteristic protected by federal, state, or local laws. See more information by clicking on the Know Your Rights: Workplace Discrimination is Illegal link.
Pay Transparency
Zscaler complies with all applicable federal, state, and local pay transparency rules.
Zscaler is committed to providing reasonable support (called accommodations or adjustments) in our recruiting processes for candidates who are differently abled, have long term conditions, mental health conditions or sincerely held religious beliefs, or who are neurodivergent or require pregnancy-related support.
Ready to apply?
Apply to Zscaler
Manager, Data Science
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About Inizio Ignite
We are Inizio Ignite, the global advisory partner for health and life sciences encompassing connected expertise across Research Partnership, Putnam, STEM, and Vynamic. Guided by purpose, passion, and precision, we collaborate with clients to ignite impact, accelerate performance, and deliver lasting change for patients. By uniting strategy, insights, and innovation with a unique depth and breadth of expertise, we drive transformation and shape the future of health. Proudly part of Inizio – the market-leading commercialization partner for health and life sciences. From early-stage development to loss of exclusivity, we simplify complexity, unlock value, and make collaboration seamless at every pivotal moment – helping healthcare leaders shape strategy and drive meaningful change.
About the Role
We are seeking an experienced Data Science Manager to join our team at Inizio Ignite. The ideal candidate will bring deep machine learning expertise, strong GenAI and cloud competencies, and hands-on experience delivering analytical solutions that drive meaningful business impact for life sciences clients.
This leader will manage data scientists, oversee project delivery, partner with cross-functional teams, and shape the development of innovative AI/ML solutions.
What you'll be doing
Leadership & Delivery
- Lead and manage a team of data scientists, providing technical guidance, mentorship, and performance oversight.
- Own end-to-end delivery of data science and GenAI engagements for pharma/biotech clients.
- Translate business problems into analytical frameworks and ensure high-quality, timely project execution.
- Drive adoption of AI/ML capabilities across client engagements and internal initiatives.
Technical Responsibilities
- Architect, design, and review ML, statistical, and GenAI solutions, ensuring scalability, accuracy, and alignment with business objectives.
- Oversee the development, validation, and deployment of predictive models, NLP pipelines, and GenAI-based applications (e.g., summarization, insights automation, generative workflows).
- Lead cloud-based solution deployment (AWS, Azure, or GCP) including orchestration, MLOps best practices, and integration with enterprise systems.
- Ensure adherence to model governance, compliance, and responsible AI frameworks.
What you'll need
- Extensive experience in data science or advanced analytics roles, with at least 2–3 years in a leadership or managerial capacity.
- Ideally prior experience in pharmaceutical, biotech, or healthcare consulting is mandatory.
- Strong expertise in machine learning, NLP, deep learning, and GenAI (LLMs, prompt engineering, RAG, fine-tuning, embeddings).
- Hands-on experience with cloud platforms such as AWS, Azure, or GCP; exposure to MLOps frameworks preferred.
- Proficiency in Python, SQL, and common DS/ML libraries (TensorFlow, PyTorch, scikit-learn, Hugging Face, LangChain, etc.).
- Proven experience managing teams, delivering client projects, and presenting to senior stakeholders.
- Good to have understanding of pharma datasets (claims, RWE, clinical, medical insights, social data) and key use cases.
- Experience building GenAI solutions in production environments
Our Pledge
At Inizio, we value inclusivity, recognize the power of diversity, and inspire the next generation of change-makers. We are an equal opportunities employer and are committed to creating a dynamic work environment that values diversity, equity, and inclusion. We welcome all applications regardless of race, color, religion, gender identity, age, national origin, marital status, veteran status, genetic information, sexual orientation, or disability.
Artificial Intelligence
Inizio may use AI technologies to support certain aspects of our recruitment process, but all hiring decisions are made by our human recruiting team. We are committed to fair, inclusive, and human-led hiring practices. Don't meet every requirement? That's okay! We are dedicated to building a diverse, inclusive, and authentic workplace. If you're excited about this role but your experience doesn't perfectly align with every qualification, we encourage you to apply anyway.
Don't meet every job requirement? That's okay! Our company is dedicated to building a diverse, inclusive, and authentic workplace. If you're excited about this role, but your experience doesn't perfectly fit every qualification, we encourage you to apply anyway. You may be just the right person for this role or others.
Ready to apply?
Apply to Inizio Ignite
Senior Full-Stack Machine Learning Engineer (GenAI / Agentic Systems)
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Introduction:
Are you searching for an opportunity to play a key role in driving the dramatic growth of a highly successful software company?
At Poppulo, we’re working on what’s next in communications and workplace technology. As a pioneer in this industry, we understand that meaningfully reaching every employee is hard. And so is managing office space in a hybrid world. And so is improving the customer and guest experience. We exist to make each of these things easier. We exist to bring harmony to our customers.
And we do that at enterprise scale. Our omnichannel employee communications, customer communications, and workplace experience platform is trusted by over 6,000 organizations today, reaching more than 35M employees and delivering content to 500,000+ digital signs.
We know there’s no such thing as a “perfect" candidate - we’re all a work in progress and are growing new skills and capabilities all the time. We encourage you to apply for a position with Poppulo even if you don’t meet 100% of the requirements. We believe in fostering an environment where there is a diversity of perspectives, in hopes that we can all thrive.
The Opportunity
We are looking for a Sr. Machine Learning (ML) Engineer with a strong sense of ownership. If you are an ML practitioner who thrives in an environment where innovation meets practical application to build disruptive products, this role is for you.
At Poppulo, we intend to redefine boundaries and reshape Employee Communications and Digital Signage through the power of cutting-edge machine learning and AI. We are not just building products; we are disrupting the status-quo with transformative solutions that challenge conventional thinking, create competitive edge and create new market opportunities.
This role is pivotal to the success of our AI team. It is the backbone of our ML initiatives. This role bridges the gap between research and production by leveraging cutting-edge AI technology into leading, world-class solutions.
As a Sr. Full-Stack Machine Learning (ML) Engineer, you be the key driver for innovative problem solving by combining technical excellence with creative application of ML. Your expertise will be crucial in uncovering hidden opportunities within product ideas, including the design and deployment of agentic AI systems that can reason, plan, and act autonomously within real-world product constraints. Additionally, you will stay at the forefront of emerging technologies, continuously evaluating new AI/ML frameworks, tools, and best practices to help guide the evolution of our software solutions.
Key Responsibilities
- Own end-to-end delivery of AI features across model, backend, APIs, UI integration, deployment, monitoring, and iteration in production
- Solve complex challenges with AI/ML: Design, develop new AI-powered products that deliver the product roadmap, including agentic AI solutions that orchestrate LLMs, tools, and workflows to solve multi-step problems autonomously.
- Implement ML lifecycle - from data engineering and model development to cloud-based deployment, integrations and operationalisation. Incl. MLOps
- Productionise full-stack AI/ML solutions: Translate emerging techs like GenAI& agenticAI architectures into innovative, practical solutions that transform customer experiences.
- Align with Product Strategy: Create proof of concepts at high cadence to demonstrate/validate potential solutions as per our product strategy.
- Optimise Model and system performance: Fine-tune, optimise training and inference performances, including latency, cost, and reliability trade-offs in agent-based and LLM-driven systems.
- Wider collaboration: Partner with cross-functional teams to demonstrate and validate the impact of ML innovations before introducing them into the product ecosystem.
- Research Savvy: Staying up-to-date with SOTA and industry trends in AI/ML, with a strong awareness of advances in agentic systems, autonomous workflows, and multi-agent architectures.
Technical Skills / Competencies
- Strong AI/ML background: Expertise in designing, building and deploying real-world ML applications (Computer Vision, Classification, etc.)
- Strong foundation in GenAI: Deep understanding of generative models (LLMs, etc.), AI Agents, prompt engineering RAG, vector databases.
- Technical Expertise: Proficiency in ML/GenAI frameworks, databases, shell scripts and programming languages, including frameworks and tools commonly used for building and orchestrating AI agents.
- MLOps expertise: Hands-on experience in setting up MLOps on AWS, Azure and GCP.
- Full-stack expertise: Proficiency in data pipelines, distributed systems, APIs, web front-end, mobile apps, automated testing and cloud platforms (AWS, GCP, etc.).
- Exceptional problem-solving skills: Ability to simplify and breakdown complex technical and business challenges to create innovative and practical solutions.
- Team management: Experience in guiding teams to deliver high-impact solutions.
- Continuous learning: Ability to learn quickly and apply new technologies to solve problems practically.
Education & Experience
- Master’s or PhD in AI/ML or a related field
- At least 6+ years of experience building software or AI systems, including 1–3 years working with LLMs, generative AI, or AI agent architectures.
Why Us?
- An excellent workplace culture
- Competitive salary
- Company performance-related bonus
- Medical insurance
- Flexible working hours
- Educational assistance
- In-house soft skills training
Who We Are
We are a values-driven organization that encourages our employees to bring their authentic selves to work every day and empowers everyone to make a tangible impact on our products, clients, and culture. We offer a dynamic environment with driven, fun, and flexible individuals who thrive on challenge and responsibility. This is an opportunity to contribute to our culture and join a company that’s on the move.
We live the Poppulo values each day, as they are key to everything we do.
- Bring Your Best Self
We show up authentically, are self-aware and always strive to be better. - See it. Own it. Solve it.
We proactively innovate and solve for our customers and each other. We set an example with high standards for our work. We foster a culture of learning, acknowledging our successes and our failures. - Together We’re Better
We value and celebrate our diversity. We learn from others, respecting their expertise, and focus on building trust. That's what makes us a team.
Named a Great Place to Work in 2015, 2016, 2017, 2018, 2019, 2020, and 2021, we are a fast-growing global technology company, with offices in Ireland, the US, the UK and India.
Poppulo is an equal opportunity employer.
We are committed to protecting your privacy. For details on how we collect, use, and protect your personal information, please refer to our Job Applicant Privacy Policy.
Ready to apply?
Apply to Poppulo
Senior Full-Stack Machine Learning Engineer (GenAI / Agentic Systems)
Share this job
Introduction:
Are you searching for an opportunity to play a key role in driving the dramatic growth of a highly successful software company?
At Poppulo, we’re working on what’s next in communications and workplace technology. As a pioneer in this industry, we understand that meaningfully reaching every employee is hard. And so is managing office space in a hybrid world. And so is improving the customer and guest experience. We exist to make each of these things easier. We exist to bring harmony to our customers.
And we do that at enterprise scale. Our omnichannel employee communications, customer communications, and workplace experience platform is trusted by over 6,000 organizations today, reaching more than 35M employees and delivering content to 500,000+ digital signs.
We know there’s no such thing as a “perfect" candidate - we’re all a work in progress and are growing new skills and capabilities all the time. We encourage you to apply for a position with Poppulo even if you don’t meet 100% of the requirements. We believe in fostering an environment where there is a diversity of perspectives, in hopes that we can all thrive.
The Opportunity
We are looking for a Sr. Machine Learning (ML) Engineer with a strong sense of ownership. If you are an ML practitioner who thrives in an environment where innovation meets practical application to build disruptive products, this role is for you.
At Poppulo, we intend to redefine boundaries and reshape Employee Communications and Digital Signage through the power of cutting-edge machine learning and AI. We are not just building products; we are disrupting the status-quo with transformative solutions that challenge conventional thinking, create competitive edge and create new market opportunities.
This role is pivotal to the success of our AI team. It is the backbone of our ML initiatives. This role bridges the gap between research and production by leveraging cutting-edge AI technology into leading, world-class solutions.
As a Sr. Full-Stack Machine Learning (ML) Engineer, you be the key driver for innovative problem solving by combining technical excellence with creative application of ML. Your expertise will be crucial in uncovering hidden opportunities within product ideas, including the design and deployment of agentic AI systems that can reason, plan, and act autonomously within real-world product constraints. Additionally, you will stay at the forefront of emerging technologies, continuously evaluating new AI/ML frameworks, tools, and best practices to help guide the evolution of our software solutions.
Key Responsibilities
- Own end-to-end delivery of AI features across model, backend, APIs, UI integration, deployment, monitoring, and iteration in production
- Solve complex challenges with AI/ML: Design, develop new AI-powered products that deliver the product roadmap, including agentic AI solutions that orchestrate LLMs, tools, and workflows to solve multi-step problems autonomously.
- Implement ML lifecycle - from data engineering and model development to cloud-based deployment, integrations and operationalisation. Incl. MLOps
- Productionise full-stack AI/ML solutions: Translate emerging techs like GenAI& agenticAI architectures into innovative, practical solutions that transform customer experiences.
- Align with Product Strategy: Create proof of concepts at high cadence to demonstrate/validate potential solutions as per our product strategy.
- Optimise Model and system performance: Fine-tune, optimise training and inference performances, including latency, cost, and reliability trade-offs in agent-based and LLM-driven systems.
- Wider collaboration: Partner with cross-functional teams to demonstrate and validate the impact of ML innovations before introducing them into the product ecosystem.
- Research Savvy: Staying up-to-date with SOTA and industry trends in AI/ML, with a strong awareness of advances in agentic systems, autonomous workflows, and multi-agent architectures.
Technical Skills / Competencies
- Strong AI/ML background: Expertise in designing, building and deploying real-world ML applications (Computer Vision, Classification, etc.)
- Strong foundation in GenAI: Deep understanding of generative models (LLMs, etc.), AI Agents, prompt engineering RAG, vector databases.
- Technical Expertise: Proficiency in ML/GenAI frameworks, databases, shell scripts and programming languages, including frameworks and tools commonly used for building and orchestrating AI agents.
- MLOps expertise: Hands-on experience in setting up MLOps on AWS, Azure and GCP.
- Full-stack expertise: Proficiency in data pipelines, distributed systems, APIs, web front-end, mobile apps, automated testing and cloud platforms (AWS, GCP, etc.).
- Exceptional problem-solving skills: Ability to simplify and breakdown complex technical and business challenges to create innovative and practical solutions.
- Team management: Experience in guiding teams to deliver high-impact solutions.
- Continuous learning: Ability to learn quickly and apply new technologies to solve problems practically.
Education & Experience
- Master’s or PhD in AI/ML or a related field
- At least 6+ years of experience building software or AI systems, including 1–3 years working with LLMs, generative AI, or AI agent architectures.
Why Us?
- An excellent workplace culture
- Competitive salary
- Company performance-related bonus
- Medical insurance
- Flexible working hours
- Educational assistance
- In-house soft skills training
Who We Are
We are a values-driven organization that encourages our employees to bring their authentic selves to work every day and empowers everyone to make a tangible impact on our products, clients, and culture. We offer a dynamic environment with driven, fun, and flexible individuals who thrive on challenge and responsibility. This is an opportunity to contribute to our culture and join a company that’s on the move.
We live the Poppulo values each day, as they are key to everything we do.
- Bring Your Best Self
We show up authentically, are self-aware and always strive to be better. - See it. Own it. Solve it.
We proactively innovate and solve for our customers and each other. We set an example with high standards for our work. We foster a culture of learning, acknowledging our successes and our failures. - Together We’re Better
We value and celebrate our diversity. We learn from others, respecting their expertise, and focus on building trust. That's what makes us a team.
Named a Great Place to Work in 2015, 2016, 2017, 2018, 2019, 2020, and 2021, we are a fast-growing global technology company, with offices in Ireland, the US, the UK and India.
Poppulo is an equal opportunity employer.
We are committed to protecting your privacy. For details on how we collect, use, and protect your personal information, please refer to our Job Applicant Privacy Policy.
Ready to apply?
Apply to Poppulo
Toast creates technology to help restaurants and local businesses succeed in a digital world, helping business owners operate, increase sales, engage customers, and keep employees happy.
Now, more than ever, the Toast team is committed to our customers. We’re taking steps to help restaurants navigate these unprecedented times with technology, resources, and community. Our focus is on building the restaurant platform that helps restaurants adapt, take control, and get back to what they do best: building the businesses they love. And because our technology is purpose-built for restaurants, by restaurant people, restaurants can trust that we’ll deliver on their needs for today while investing in experiences that will power their restaurant of the future.
Bready* to make a change?
Toast is looking for a Staff Machine Learning Engineer to serve as a technical linchpin for our AI Platform team. At the P4 level, you aren't just deploying models; you are designing the fundamental infrastructure that enables dozens of teams to build, deploy, and monitor AI at scale. You will act as a force multiplier, mentoring senior engineers and setting the architectural standards for our MLOps lifecycle—from feature stores and automated retraining to high-performance inference at the edge.
About this Roll*:
- Architectural Leadership: Design and lead the evolution of a unified MLOps platform that supports diverse needs across Toast, ensuring high availability, scalability, and security of ML services.
- Engineering Excellence: Champion and institutionalize best practices for CI/CD for ML (MLOps), automated testing, and infrastructure-as-code (Terraform).
- Cross-Functional Synergy: Lead collaborative efforts across Data Engineering, DevOps, and Product teams to bridge the gap between model prototyping and production-grade reliability.
- Strategic Roadmapping: Partner with leadership and Product Managers to define the 1-2 year technical vision for AI infrastructure, prioritizing long-term stability over short-term fixes.
- Operational Ownership: Set the standard for observability and incident response for ML systems, driving root-cause analysis for complex system failures.
- Mentorship: Actively mentor P2 and P3 engineers, fostering a culture of technical rigor and continuous learning.
Do you have the right ingredients*?
- Education: Bachelor’s or Master’s degree in Computer Science, AI, or a related technical field.
- Experience: A minimum of 10-12+ years of professional software engineering experience, with at least 6-7 years specifically focused on productionizing and scaling ML systems at the enterprise level.
- Core Tech Stack: Expert-level proficiency in Python, Scala, or Java/Kotlin. Extensive experience with PySpark and high-performance computing.
- Generative AI & LLMOps: Proven track record of taking LLM applications from research to production, including experience with Vector Databases, LangChain/LangGraph, and A2A protocols.
- System Design: Superior ability to design distributed systems that handle millions of requests with sub-second latency.
- Experience with microservice based architecture, preferably with AWS tooling (SageMaker, DynamoDB, Athena, Glue, etc.)
- Experience in software engineering best practices and tools including object-oriented programming, test-driven development, CI/CD, git, shell scripting, task orchestration, MLflow
- Profound knowledge of model deployment, orchestration (Apache airflow, Prefect), scaling, and managing CPU/GPU resources efficiently.
- Exceptional problem-solving, analytical skills and the ability to tackle complex problems with a critical thinking approach.
- Outstanding communication and interpersonal skills, coupled with a demonstrated ability to work collaboratively within a team environment.
- Foundational knowledge in statistical concepts (e.g. classification, regression, etc) and deep learning algorithms (e.g. CNN, RNN) is desirable
Bonus Ingredients (The "Staff" Edge)
- Data Strategy: Experience implementing enterprise-grade Feature Stores (e.g., Tecton, Feast) and real-time streaming frameworks like Apache Flink or Ray.
- Full-Stack Visibility: Ability to dive into the UI/UX layer (React) or deep into the kernel/networking layer to debug performance bottlenecks.
Open Source/Community: Contributions to relevant open-source projects (MLflow, Kubeflow, etc.) or a history of speaking at industry conferences.
AI at Toast
At Toast, one of our company values is that we're hungry to build and learn. We believe learning new AI tools empowers us to build for our customers faster, more independently, and with higher quality. We provide these tools across all disciplines, from Engineering and Product to Sales and Support, and are inspired by how our Toasters are already driving real value with them. The people who thrive here are those who embrace changes that let us build more for our customers; it’s a core part of our culture.
Our Total Rewards Philosophy
We strive to provide competitive compensation and benefits programs that help to attract, retain, and motivate the best and brightest people in our industry. Our total rewards package goes beyond great earnings potential and provides the means to a healthy lifestyle with the flexibility to meet Toasters’ changing needs. Learn more about our benefits at https://careers.toasttab.com/toast-benefits.
How Toast Uses AI in its Hiring Process
Throughout the hiring process, our goal is to get to know you. We use AI tools to support our recruiters and interviewers with tasks like note-taking, summarization, and documentation of interviews to ensure they can be fully focused on your conversation. All hiring decisions are made by people. To learn more: https://careers.toasttab.com/ai-in-hiring
Diversity, Equity, and Inclusion is Baked into our Recipe for Success
At Toast, our employees are our secret ingredient—when they thrive, we thrive. The restaurant industry is one of the most diverse, and we embrace that diversity with authenticity, inclusivity, respect, and humility. By embedding these principles into our culture and design, we create equitable opportunities for all and raise the bar in delivering exceptional experiences.
We Thrive Together
We embrace a hybrid work model that fosters in-person collaboration while valuing individual needs. Our goal is to build a strong culture of connection as we work together to empower the restaurant community. To learn more about how we work globally and regionally, check out: https://careers.toasttab.com/locations-toast.
Apply today!
Toast is committed to creating an accessible and inclusive hiring process. As part of this commitment, we strive to provide reasonable accommodations for persons with disabilities to enable them to access the hiring process. If you need an accommodation to access the job application or interview process, please contact candidateaccommodations@toasttab.com.
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For roles in the United States, it is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.
Ready to apply?
Apply to Toast
Job Title: GenAI Developer/ Engineer
About Us
“Capco, a Wipro company, is a global technology and management consulting firm. Awarded with Consultancy of the year in the British Bank Award and has been ranked Top 100 Best Companies for Women in India 2022 by Avtar & Seramount. With our presence across 32 cities across globe, we support 100+ clients across banking, financial and Energy sectors. We are recognized for our deep transformation execution and delivery.
WHY JOIN CAPCO?
You will work on engaging projects with the largest international and local banks, insurance companies, payment service providers and other key players in the industry. The projects that will transform the financial services industry.
MAKE AN IMPACT
Innovative thinking, delivery excellence and thought leadership to help our clients transform their business. Together with our clients and industry partners, we deliver disruptive work that is changing energy and financial services.
#BEYOURSELFATWORK
Capco has a tolerant, open culture that values diversity, inclusivity, and creativity.
CAREER ADVANCEMENT
With no forced hierarchy at Capco, everyone has the opportunity to grow as we grow, taking their career into their own hands.
DIVERSITY & INCLUSION
We believe that diversity of people and perspective gives us a competitive advantage.
Location - Bangalore
Experience - 6 to 10
Skills and Qualifications:
Preferred skills:
Programming: Advanced Python (async programming, OOP, REST APIs, FastAPI, Flask, Pandas, NumPy)
GenAI Frameworks: LangChain, LlamaIndex, Haystack, Semantic Kernel
Machine Learning and AI: Snowflake Cortex, TensorFlow, PyTorch
Key Responsibilities:
- Develop scalable Python applications focused on GenAI
- Knowledge of Snowflake Cortex is a big plus.
- Learn and apply techniques like document chunking and embeddings
- Proficient in both SQL (e.g., PostgreSQL, MySQL) and NoSQL (e.g., MongoDB, Cassandra) databases, including schema design and optimization.
- Design, develop, and fine-tune applications built around foundation models (e.g., LLMs, multimodal models) for specific business needs
- Implement and experiment with generative AI techniques, including but not limited to Retrieval-Augmented Generation (RAG) and prompt engineering
- Lead the implementation of intelligent autonomous agents and multi-agent systems capable of complex decision-making, task execution, and interaction with external systems
- Utilize and contribute to agentic AI frameworks (e.g., LangChain, AutoGen, Semantic Kernel, Crew AI) to build robust and scalable AI agents
- Develop and integrate Model Context Protocol (MCP) solutions to standardize how AI applications access and utilize external data sources, tools, and real-time information
- Lead the development of full-stack applications that integrate generative AI models and agentic systems, ensuring seamless user experiences
- Work with front-end technologies (e.g., React, Angular, Vue.js, JavaScript, TypeScript, HTML, CSS) and back-end frameworks (e.g., Python with Flask/Django/FastAPI, Node.js, Go)
- Design and implement scalable RESTful APIs and microservices to expose AI functionalities
- Deploy, manage, and optimize AI/ML workloads and full-stack applications on at least one major cloud platform (AWS, Azure, or GCP)
- Implement LLMOps/MLOps and DevOps best practices for continuous integration, continuous delivery (CI/CD), model deployment, monitoring, and lifecycle management
- Follow coding best practices and contribute to testing and documentation
- Stay abreast of the latest advancements in generative AI, agentic systems, foundation models, and related fields through continuous research and experimentation
- Collaborate effectively with cross-functional teams, including product managers, data scientists, researchers, and other engineers
- Communicate effectively with both technical and non-technical team members, ensuring alignment and understanding across all project phases.
Ready to apply?
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Staff Software Engineer – Full Stack & AI Innovation
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About Gruve
Gruve is an innovative software services startup dedicated to transforming enterprises to AI powerhouses. We specialize in cybersecurity, customer experience, cloud infrastructure, and advanced technologies such as Large Language Models (LLMs). Our mission is to assist our customers in their business strategies utilizing their data to make more intelligent decisions. As a well-funded early-stage startup, Gruve offers a dynamic environment with strong customer and partner networks.
Position Summary:
We are looking for a Staff Software Engineer – Full Stack & AI Innovation with strong hands-on experience in TypeScript (Node.js, JavaScript), and/or Python and a passion for leveraging AI-driven code generation tools to accelerate development. You will play a critical role in operationalizing GenAI-based code generation platform. This role involves translating product specifications into structured inputs for GenAI tools, reviewing the code generated by GenAI tool, and providing feedback to product engineering team to improve quality and performance of the GenAI tool.
You will work closely with product managers, software engineers, and AI specialists to ensure that the generated code aligns with business and technical requirements. The ideal candidate is curious, adaptable, critic and eager to evaluate AI-assisted code generation tool.
Key Responsibilities:
- Develop, Analyze and structure product specifications for input into GenAI programming tools.
- Operate GenAI systems to generate code based on structured inputs.
- Perform detailed code reviews of GenAI-generated programs to ensure correctness, performance, and maintainability.
- Utilize several other AI-powered code generation tools (Cursor.ai, Windsurf, etc.) to compare and optimize GenAI tool in subject.
- Provide feedback to improve GenAI model outputs and prompt engineering strategies.
- Review and validate generated code for correctness, efficiency, and adherence to coding standards.
- Maintain documentation of input formats, code review findings, and feedback cycles.
- Stay current with advancements in GenAI programming tools and code generation technologies.
- Participate in code reviews and mentor junior developers.
Basic Qualifications:
- Bachelor’s/master’s in computer science, Engineering, or equivalent experience.
- 8 to 10 years' experience with strong expertise in at least one of the following:
- TypeScript / JavaScript (Node.js, React, Next.js, Angular, Vue.js)
- Python (Django, Flask, FastAPI/ RestAPI)
- Person must have designed, developed, and maintained scalable front-end and back-end applications using TypeScript/JavaScript/Python.
- Solid understanding of front-end technologies (HTML5, CSS3, Tailwind, Material UI or similar).
- Familiarity with GenAI tools and LLM-based code generation platforms (e.g., GitHub Copilot, CodeWhisperer, etc.).
- Experience with databases: SQL (PostgreSQL, MySQL) and NoSQL (MongoDB, DynamoDB).
- Hands-on experience with Cursor.ai and/or Windsurf (plus other AI-assisted coding tools like GitHub Copilot, Tabnine, Codeium).
- Strong understanding of software development principles and code review practices.
- Familiar with Code review tools (e.g. GitHub, GitLab, Bitbucket etc)
- Strong grasp of software design principles (OOP, SOLID, microservices).
- Excellent problem-solving, debugging, and collaboration skills.
- Excellent analytical and communication skills.
- Ability to work independently and collaboratively in a fast-paced environment.
Preferred Qualifications:
- Experience working with prompt engineering or structured input design for GenAI systems.
- Exposure to MLOps or AI model evaluation frameworks.
- Knowledge of software architecture and design patterns.
- Knowledge of containerization (Docker, Kubernetes).
- Exposure to serverless architecture and event-driven systems.
- Contribution to open-source or AI-driven development communities.
Why Gruve
At Gruve, we foster a culture of innovation, collaboration, and continuous learning. We are committed to building a diverse and inclusive workplace where everyone can thrive and contribute their best work. If you’re passionate about technology and eager to make an impact, we’d love to hear from you.
Gruve is an equal opportunity employer. We welcome applicants from all backgrounds and thank all who apply; however, only those selected for an interview will be contacted.
Ready to apply?
Apply to Gruve
A career that’s the whole package!
At Conga, we’ve built a community where our colleagues can thrive. Here you’ll find opportunities to innovate and support growth through individual and team development, all within an environment where every voice is heard.
Conga lines up commercial operations so companies run as connected, smarter businesses. By unifying the people and processes that drive commerce, Conga aligns pricing, quoting, contracting, rebates, and communications so teams stay in sync and buyers keep moving forward. The result is trusted decisions, consistent buyer experiences, and profitable growth. More than 10,000 customers worldwide, including over 50% of the Fortune 100®, trust Conga when commercial complexity is high and global impact is on the line.
Our approach is grounded in the Conga Way, a framework that reflects our values and drives everything from hiring to decision-making, as well as key programs including recognition. Created with direct input from our colleagues, the Conga Way forms the foundation of our vibrant culture.
Job Title: Associate Software Engineer, AI
Location: Bangalore
Reports to: Sr. Manager, AI/ML
A quick snapshot…
As an Associate Software Engineer, you’ll be working on developing robust solutions across next-generation AI/GenAI based products and solutions. As a critical member of our team, you will play a pivotal role in enhancing our design, development, and continued enhancement of our features along with writing unit & integration tests to ensure features never break.
Why it’s a big deal…
This is one of the critical roles under the AI team within Engineering. You will possess deep technical expertise as a AI engineer and a strong commitment to participate in the entire AI development lifecycle, including data collection, preprocessing, model training, evaluation, and deployment. This role works on multiple technologies and databases to make sure the product development moves towards rapid development, rich controls, more scalable, and better security.
Are you the person we’re looking for?
Related Experience. You should have at least 6 Months of experience in the software industry as a AI Engineer and the technical requirements necessary to design, develop, test and implement solutions.
Technical Skills. You’re likely to have proficiency in AI development technologies such as Python, FastAPI, PyTest, Celery and other Python frameworks and familiarity with AI/ML, GenAI, and MLOps concepts. You also possess good understanding with object-oriented programming, concurrency, design patterns, and REST APIs. Your familiarity with CI/CD tooling such as Terraform and GitHub Actions and frameworks like LangChain, LangGraph, and databases like SQL and NoSQL such as MongoDB, MSSQL, or Postgres. Understanding of Data Structure & Algorithm analysis and its usage in scalable software design.
Strong communication and interpersonal skills. You’re not just comfortable engaging in collaborative discussions, but initiating them, too. You are skilled at reading and adapting to different communication styles. When you speak you are clear and concise. Your strong listening skills foster connections with our clients and allow you to accurately collect the right information so you can resolve issues most expediently.
Education. A bachelor’s degree in engineering or equivalent.
Here’s what will give you an edge…
Initiative. You don’t wait around for things to happen or for your manager to tell you what to do. You’re not only proactive about completing your work, but when you sense the need to introduce a project that will benefit the team or the organization -- even if it’s outside your scope of work -- you put a proposal together, talk to the team about it, and own it. And that also goes back to having an entrepreneurial spirit.
Strong troubleshooting skills and logic based thinking is your forte. This is an absolute must. Your proven ability to analyze and apply logical thinking to determine the root cause of an issue is fundamental to success in this role.
Clear, deliberate, and collaborative communicator. You don’t just engage in collaborative discussions, you initiate them regularly. You are clear and concise when you speak and write -- and even creative in terms of ensuring your messages are received and understood. You leave no room for assumptions or misunderstanding. It’s what sets you apart from the rest.
Exposure to mature SDLC practices. Understanding of Agile methodologies. Experience with unit testing, code coverage, and security scan tools. Proficient in working with source control tools like GitHub/Bitbucket.
#LI-RT1
Did we pique your interest?
If this sounds like the kind of job you would love in the kind of environment where you would thrive, please click apply. We'd love to hear from you!
Preferred Resume Format
We accept resumes in any format, we suggest using PDF or plain text. These formats help ensure that your resume’s formatting remains intact, making it easier for our recruiters to review your application promptly.
Don’t meet every requirement for the role?
Studies have shown that women and members of ethnic minorities are less likely to apply to jobs unless they meet every single qualification. At Conga we are dedicated to building a diverse, inclusive, and authentic workplace, so if you’re excited about this role but your experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyway. You just might be the right candidate for this or other roles.
Additional Information
Conga is proud to be an Equal Opportunity Employer and provides equal employment opportunities to all employees and applicants regardless of race, color, religion, gender, gender identity, age, national origin, disability, parental or pregnancy status, marriage and civil partnership, sexual orientation, veteran status, or any other characteristic protected by law. We understand interviewing can be stressful for those with disabilities. If reasonable accommodation is needed to allow you to show us your best self, please let your recruiter know as soon as possible. All your information will be kept confidential according to EEO guidelines. Conga is not open to third party solicitation or resumes for our posted FTE positions. Resumes received from third party agencies that are unsolicited will be considered complimentary.
Conga's Applicant Privacy Statement
The information you provide during the application process will be used in accordance with Conga’s Applicant Privacy Statement (https://conga.com/applicant-privacy-statement). By submitting your application, you acknowledge and agree to the terms outlined in this privacy statement.
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At Anaplan, we are a team of innovators focused on optimizing business decision-making through our leading AI-infused scenario planning and analysis platform so our customers can outpace their competition and the market.
What unites Anaplanners across teams and geographies is our collective commitment to our customers’ success and to our Winning Culture.
Our customers rank among the who’s who in the Fortune 50. Coca-Cola, LinkedIn, Adobe, LVMH and Bayer are just a few of the 2,400+ global companies who rely on our best-in-class platform.
Our Winning Culture is the engine that drives our teams of innovators. We champion diversity of thought and ideas, we behave like leaders regardless of title, we are committed to achieving ambitious goals, and we love celebrating our wins – big and small.
Supported by operating principles of being strategy-led, values-based and disciplined in execution, you’ll be inspired, connected, developed and rewarded here. Everything that makes you unique is welcome; join us and let’s build what’s next - together!
Key Responsibilities
- Lead, mentor, and grow a high-performing team of AI/ML engineers, fostering a culture of innovation, collaboration, and excellence.
- Define and execute the roadmap for AI/ML projects, ensuring alignment with business objectives and product strategy.
- Architect and oversee the development of scalable, robust, and production-grade AI systems on cloud platforms (AWS, Azure, GCP).
- Drive best practices for the full machine learning lifecycle, including MLOps, CI/CD for ML, model monitoring, and governance.
- Collaborate closely with product managers, data scientists, and other engineering leaders to translate business requirements into technical solutions.
- Stay at the forefront of advancements in AI/ML, including Large Language Models (LLMs) and agentic AI, to identify and implement new opportunities.
- Manage project timelines, resources, and stakeholder communication to ensure the timely delivery of high-quality AI solutions.
Required Qualifications
- Strong understanding or experience leading AI/ML teams in a SaaS or enterprise software environment.
- Deep expertise in time series forecasting and machine learning.
- Experience architecting and deploying scalable, production-grade AI systems on cloud platforms (AWS, Azure, GCP).
- Solid understanding of MLOps, CI/CD for ML, and cloud-native architectures.
- Deep knowledge of LLM APIs, prompt engineering, and conversational AI patterns.
- Experience with agentic frameworks and autonomous agent architectures.
- Proficiency in Python and modern software development practices (testing, code review, CI/CD).
- Proven track record of delivering complex technical projects on time with high quality.
- Excellent communication, collaboration, and stakeholder management skills.
- Track record of delivering impactful AI solutions in a fast-paced, agile environment.
Preferred Qualifications
- Master’s or Ph.D. in Computer Science, AI, Machine Learning, or a related field.
- Experience with large-scale data processing frameworks like Spark.
- Familiarity with the challenges of applying AI in enterprise planning or financial domains.
- A portfolio of published research or contributions to open-source AI projects.
What Makes This Role Exciting
You will be a key leader in Anaplan’s AI journey, with the autonomy to shape our technical direction and build a world-class engineering team. This is a unique opportunity to solve complex, real-world problems and deliver intelligent solutions that empower major global enterprises to make more informed decisions. You will work with a passionate team on the cutting edge of AI, making a tangible impact on our product and the industry.
Our Commitment to Diversity, Equity, Inclusion and Belonging (DEIB)
We believe attracting and retaining the best talent and fostering an inclusive culture strengthens our business. DEIB improves our workforce, enhances trust with our partners and customers, and drives business success. Build your career in a place where diversity, equity, inclusion and belonging aren’t just words on paper – this is what drives our innovation, it’s how we connect, and it contributes to what makes us a market leader. We believe in a hiring and working environment where all people are respected and valued, regardless of gender identity or expression, sexual orientation, religion, ethnicity, age, neurodiversity, disability status, citizenship, or any other aspect which makes people unique. We hire you for who you are, and we want you to bring your authentic self to work every day!
We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, perform essential job functions, and receive equitable benefits and all privileges of employment. Please contact us to request accommodation.
Fraud Recruitment Disclaimer
It has come to our attention that fraudulent and fictitious job opportunities are being circulated on the Internet. Prospective candidates are being contacted by certain individuals, mainly through telephone calls, emails and correspondence, claiming they are representatives of Anaplan. The main purpose of these correspondences and announcements is to obtain privileged information from individuals.
Anaplan does not:
- Extend offers to candidates without an extensive interview process with a member of our recruitment team and a hiring manager via video or in person.
- Send job offers via email. All offers are first extended verbally by a member of our internal recruitment team whenever possible and then followed up via written communication.
All emails from Anaplan would come from an @anaplan.com email address. Should you have any doubts about the authenticity of an email, letter or telephone communication purportedly from, for, or on behalf of Anaplan, please send an email to people@anaplan.com before taking any further action in relation to the correspondence.
Ready to apply?
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Manager, AI/ML Ops Engineering (Hybrid in Bangalore)
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For over 20 years, Smartsheet has helped people and teams achieve–well, anything. From seamless work management to smart, scalable solutions, we’ve always worked with flow. We’re building tools that empower teams to automate the manual, uncover insights, and scale smarter. But more than that, we’re creating space– space to think big, take action, and unlock the kind of work that truly matters. Because when challenge meets purpose, and passion turns into progress, that’s magic at work, and it’s what we show up for everyday.
For over 20 years, Smartsheet has helped people and teams achieve–well, anything. As the Intelligent Work Management Platform, we are redefining the velocity of work by uniting people, data, and AI to move businesses forward. We don’t just automate tasks; we eliminate execution silos and turn strategic vision into measurable enterprise impact. We’re creating a space to think big and take action, because when challenge meets purpose and AI-powered execution meets human ingenuity, that’s magic at work. It’s what we show up for every day, helping organizations not just keep up with change, but thrive because of it.
Our India Global Capability Center isn't just supporting global operations—we’re leading global innovation. After scaling rapidly into a best-in-class hub, we deliver the product innovation and enterprise capabilities that accelerate our global growth, profitability, and scale. As we expand Smartsheet India, we’re searching for Manager AI/ML Ops Engineering, who crave variety and ownership. You’ll have the opportunity to work across multiple teams and disciplines, building a versatile skillset while solving the complex challenges of a global platform.
You Will:
- Focus on team members and coaching them to play to their strengths, grow and deliver peak performance
- Lead and mentor a team of AI/ML Ops engineers and operations specialists.
- Define and govern solutions for AI/ML operations, ensuring scalability, cost-efficiency, and reliability
- Develop and maintain standardized AI/MLOps workflows, including CI/CD/CT (Continuous Integration/Continuous Delivery/Continuous Training) pipelines
- Delegate and harness the aggregate strength of your team.
- Focuses on individual and team needs to foster a positive culture consistent with Smartsheet values.
- Actively helps individuals and the overall team to set priorities and focus on delivery of commitments
- Review team's designs and provide feedback on deployment safety, resilience, scale, performance, and security
- Lead and facilitate cross-team interactions, communication, and dependencies
- Ensure all changes are fully tested before being deployed
- Ensure deployment plans are well-considered and include appropriate scalability and load tests
- Work with stakeholders to align AI projects with business strategies.
- Ensure all AI/ML Ops solutions adhere to regulatory compliance, security, and ethical guidelines
- Drive Engineering and Operational excellence initiatives
- Perform other duties as assigned
You Have:
- Enterprise SaaS software solutions with high availability and scalability
- Experience building teams through recruiting and retention
- Experience in Leading and Mentoring a team of ML engineers and operations specialists.
- Experience in building and maintaining AI/ML Ops platform systems ensuring scalability, reliability, efficiency and security
- AI/MLOps workflows on Databricks , MLFlow, Mosaic AI Agent Framework, Unity Catalog, Vector Search, Knowledge Graph
- Knowledge of AI/ML frameworks like LangChain, LangGraph for AI/ML Ops pipeline integration
- Cloud Platforms: Hands-on experience with at least one major cloud provider (AWS, Azure, or GCP). Experience in AWS hosted data platform is preferable
- Programming languages like Python and SQL
- Modern software engineering practices like Kubernetes, CI/CD, IAC tools (Preferably Terraform), Observability, monitoring and alerting
- Solution Cost Optimisations and design to cost
- Legally eligible to work in India on an ongoing basis
Get to Know Us:
At Smartsheet, your ideas are heard, your potential is supported, and your contributions have real impact. You’ll have the freedom to explore, push boundaries, and grow beyond your role. We welcome diverse perspectives and nontraditional paths—because we know that impact comes from individuals who care deeply and challenge thoughtfully. When you’re doing work that stretches you, excites you, and connects you to something bigger, that’s magic at work. Let’s build what’s next, together.
Equal Opportunity Employer:
Smartsheet is an Equal Opportunity (EEO) employer committed to fostering an inclusive environment with the best employees. It is our policy to provide equal employment opportunities to all qualified applicants in accordance with applicable laws in the US, UK, Australia, Germany, Costa Rica, Japan, Bulgaria, and India. All qualified applicants will receive consideration without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, protected veteran or disabled status, or genetic information.
If there are preparations we can make to help ensure you have a comfortable and positive interview experience, please let us know.
#LI-Remote
Ready to apply?
Apply to Smartsheet
Senior AI/ML Ops Engineer-II (Hybrid in Bangalore)
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For over 20 years, Smartsheet has helped people and teams achieve–well, anything. From seamless work management to smart, scalable solutions, we’ve always worked with flow. We’re building tools that empower teams to automate the manual, uncover insights, and scale smarter. But more than that, we’re creating space– space to think big, take action, and unlock the kind of work that truly matters. Because when challenge meets purpose, and passion turns into progress, that’s magic at work, and it’s what we show up for everyday.
Our India Global Capability Center isn't just supporting global operations—we’re leading global innovation. After scaling rapidly into a best-in-class hub, we deliver the product innovation and enterprise capabilities that accelerate our global growth, profitability, and scale. As we expand Smartsheet India, we’re searching for Senior AI/ML Ops Engineers who crave variety and ownership. You’ll have the opportunity to work across multiple teams and disciplines, building a versatile skillset while solving the complex challenges of a global platform.
You Will:
- Designing, Developing and overseeing the strategy and architecture of scalable and reliable AI/ML Ops platforms / pipelines
- Model Deployment: Package and deploy AI/ML services to production, ensuring they are reproducible and interpretable
- CI/CD Pipeline Development: Design and implement automated CI/CD (Continuous Integration/Continuous Deployment) pipelines to accelerate model deployment using tools
- Infrastructure Management: Provision and optimize infrastructure for training and serving, utilizing Docker, Kubernetes, or serverless platforms
- Monitoring & Observability : Implement post-deployment monitoring for model performance, data drift, and latency using tools. Experience in Monte Carlo is preferable
- Automation: Automate retraining and data pipeline workflows to ensure models stay accurate over time.
- Manage the deployment of foundation models, fine-tuning workflows, and Retrieval-Augmented Generation (RAG) stacks (Vector DBs, Knowledge Graph. Experience with AWS Bedrock is preferable
- Resource Optimization: Manage GPU/CPU utilization to minimize cloud costs while maintaining low-latency inference for users
- Collaboration: Work closely with data scientists, data engineers, and software engineers to bridge the gap between model development and production.
- Version Control & Governance: Manage versioning for data, code, and models using tools like MLflow.
- Security & Compliance: Implementing data security measures, ensuring compliance with data governance policies, and protecting sensitive data
- Technology Evaluation and Innovation: Staying abreast of emerging data technologies and exploring opportunities for innovation to improve the organisation’s data infrastructure
- Troubleshooting and Problem Solving: Diagnosing and resolving complex data-related issues, ensuring the stability and reliability of the data platform
- Perform other duties as assigned
You Have:
- Enterprise SaaS software solutions with high availability and scalability
- Solution handling large scale structured and unstructured data from varied data sources
- Experience in building and maintaining AI/ML Ops platform systems ensuring scalability, reliability, efficiency and security
- Working with Product engineering team to influence designs with data, AI and analytics use cases in mind
- In depth experience in System design, AI/ML Frameworks and tools involving large Petabytes of data with Databricks Lakehouse ecosystem
- AI/MLOps workflows on Databricks , MLFlow, Mosaic AI Agent Framework, Unity Catalog, Vector Search, Knowledge Graph
- Knowledge of AI/ML frameworks like LangChain, LangGraph for AI/ML Ops pipeline integration
- Cloud Platforms: Hands-on experience with at least one major cloud provider (AWS, Azure, or GCP). Experience in AWS hosted data platform is preferable
- Programming languages like Python and SQL
- Modern software engineering practices like Kubernetes, CI/CD, IAC tools (Preferably Terraform), Observability, monitoring and alerting
- Solution Cost Optimisations and design to cost
- Legally eligible to work in India on an ongoing basis
Get to Know Us:
At Smartsheet, your ideas are heard, your potential is supported, and your contributions have real impact. You’ll have the freedom to explore, push boundaries, and grow beyond your role. We welcome diverse perspectives and nontraditional paths—because we know that impact comes from individuals who care deeply and challenge thoughtfully. When you’re doing work that stretches you, excites you, and connects you to something bigger, that’s magic at work. Let’s build what’s next, together.
Equal Opportunity Employer:
Smartsheet is an Equal Opportunity (EEO) employer committed to fostering an inclusive environment with the best employees. It is our policy to provide equal employment opportunities to all qualified applicants in accordance with applicable laws in the US, UK, Australia, Germany, Costa Rica, Japan, Bulgaria, and India. All qualified applicants will receive consideration without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, protected veteran or disabled status, or genetic information.
If there are preparations we can make to help ensure you have a comfortable and positive interview experience, please let us know.
#LI-Remote
Ready to apply?
Apply to Smartsheet
Senior AI/ML Ops Engineer (Hybrid in Bangalore)
Share this job
For over 20 years, Smartsheet has helped people and teams achieve–well, anything. From seamless work management to smart, scalable solutions, we’ve always worked with flow. We’re building tools that empower teams to automate the manual, uncover insights, and scale smarter. But more than that, we’re creating space– space to think big, take action, and unlock the kind of work that truly matters. Because when challenge meets purpose, and passion turns into progress, that’s magic at work, and it’s what we show up for everyday.
Our India Global Capability Center isn't just supporting global operations—we’re leading global innovation. After scaling rapidly into a best-in-class hub, we deliver the product innovation and enterprise capabilities that accelerate our global growth, profitability, and scale. As we expand Smartsheet India, we’re searching for Senior AI/ML Ops Engineers who crave variety and ownership. You’ll have the opportunity to work across multiple teams and disciplines, building a versatile skillset while solving the complex challenges of a global platform.
You Will:
- Designing, Developing and overseeing the strategy and architecture of scalable and reliable AI/ML Ops platforms / pipelines
- Model Deployment: Package and deploy AI/ML services to production, ensuring they are reproducible and interpretable
- CI/CD Pipeline Development: Design and implement automated CI/CD (Continuous Integration/Continuous Deployment) pipelines to accelerate model deployment using tools
- Infrastructure Management: Provision and optimize infrastructure for training and serving, utilizing Docker, Kubernetes, or serverless platforms
- Monitoring & Observability : Implement post-deployment monitoring for model performance, data drift, and latency using tools. Experience in Monte Carlo is preferable
- Automation: Automate retraining and data pipeline workflows to ensure models stay accurate over time.
- Manage the deployment of foundation models, fine-tuning workflows, and Retrieval-Augmented Generation (RAG) stacks (Vector DBs, Knowledge Graph. Experience with AWS Bedrock is preferable
- Resource Optimization: Manage GPU/CPU utilization to minimize cloud costs while maintaining low-latency inference for users
- Collaboration: Work closely with data scientists, data engineers, and software engineers to bridge the gap between model development and production.
- Version Control & Governance: Manage versioning for data, code, and models using tools like MLflow.
- Security & Compliance: Implementing data security measures, ensuring compliance with data governance policies, and protecting sensitive data
- Technology Evaluation and Innovation: Staying abreast of emerging data technologies and exploring opportunities for innovation to improve the organisation’s data infrastructure
- Troubleshooting and Problem Solving: Diagnosing and resolving complex data-related issues, ensuring the stability and reliability of the data platform
- Perform other duties as assigned
You Have:
- Enterprise SaaS software solutions with high availability and scalability
- Solution handling large scale structured and unstructured data from varied data sources
- Experience in building and maintaining AI/ML Ops platform systems ensuring scalability, reliability, efficiency and security
- Working with Product engineering team to influence designs with data, AI and analytics use cases in mind
- In depth experience in System design, AI/ML Frameworks and tools involving large Petabytes of data with Databricks Lakehouse ecosystem
- AI/MLOps workflows on Databricks , MLFlow, Mosaic AI Agent Framework, Unity Catalog, Vector Search, Knowledge Graph
- Knowledge of AI/ML frameworks like LangChain, LangGraph for AI/ML Ops pipeline integration
- Cloud Platforms: Hands-on experience with at least one major cloud provider (AWS, Azure, or GCP). Experience in AWS hosted data platform is preferable
- Programming languages like Python and SQL
- Modern software engineering practices like Kubernetes, CI/CD, IAC tools (Preferably Terraform), Observability, monitoring and alerting
- Solution Cost Optimisations and design to cost
- Legally eligible to work in India on an ongoing basis
Get to Know Us:
At Smartsheet, your ideas are heard, your potential is supported, and your contributions have real impact. You’ll have the freedom to explore, push boundaries, and grow beyond your role. We welcome diverse perspectives and nontraditional paths—because we know that impact comes from individuals who care deeply and challenge thoughtfully. When you’re doing work that stretches you, excites you, and connects you to something bigger, that’s magic at work. Let’s build what’s next, together.
Equal Opportunity Employer:
Smartsheet is an Equal Opportunity (EEO) employer committed to fostering an inclusive environment with the best employees. It is our policy to provide equal employment opportunities to all qualified applicants in accordance with applicable laws in the US, UK, Australia, Germany, Costa Rica, Japan, Bulgaria, and India. All qualified applicants will receive consideration without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, protected veteran or disabled status, or genetic information.
If there are preparations we can make to help ensure you have a comfortable and positive interview experience, please let us know.
#LI-Remote
Ready to apply?
Apply to Smartsheet
Sr. Machine Learning Operations Engineer
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For over 20 years, Smartsheet has helped people and teams achieve–well, anything. From seamless work management to smart, scalable solutions, we’ve always worked with flow. We’re building tools that empower teams to automate the manual, uncover insights, and scale smarter. But more than that, we’re creating space– space to think big, take action, and unlock the kind of work that truly matters. Because when challenge meets purpose, and passion turns into progress, that’s magic at work, and it’s what we show up for everyday.
Smartsheet is hiring a Senior Machine Learning Operations Engineer to architect our machine learning production lifecycle. Your mission is to maintain and deploy ML models to a scalable, reliable, and secure production environment. You will design and maintain the infrastructure, automation, and monitoring systems that ensure our AI products are high-performing and cost-effective.
You will report to our Director, Analytics Engineering & Data Governance and work from our Bangalore, India office.
You Will:
Model and Pipeline Automation
- Automate the deployment and retraining of ML models, from training through to production inference, by building and managing complete CI/CD/CT (Continuous Training) pipelines, adhering to MLOps best practices.
- Build, fine-tune, or use pre-trained LLMs, deep learning models or traditional machine learning models.
- Evaluate and recommend AI or ML solutions for the product using any combination of vendor solutions and/or custom-built models.
Governance & Compliance
- Implement model versioning, lineage tracking, and auditing to ensure compliance with security and ethical standards.
Performance Monitoring
- Continuously monitor the health and performance of production machine learning models, proactively identifying and correcting model drift, staleness, and performance degradation.
- Incorporate user feedback for iterative improvements and manage necessary model retraining cycles.
Cross-Functional Collaboration
- Act as the "glue" between Data Scientists (who build models) and Software Engineers (who consume them).
- Partner effectively with software engineers, product managers and business functions to integrate the machine learning solutions across smartsheet.
Architecture and Infrastructure Management
- Provision and manage scalable cloud infrastructure using Infrastructure as Code (IaC).
- Provide architectural guidance and mentorship to a team consisting of ML engineers, data scientists and analytics engineers.
- Distill complex ML concepts into easy-to-follow technical documentation.
You Have:
- 5+ years of experience with creating, deploying and scaling machine learning solutions in a cloud environment (eg. AWS, GCP, Azure) and ability to use tools such as SageMaker, Glue, Lambda, Docker etc. to create ML models and data pipelines.
- 7+ years of programming experience in languages used in AI/ML (eg python, scala etc)
- 4+ years of experience in developing deep learning and traditional ML models using common frameworks like pytorch, tensorflow, huggingface, scikit-learn etc.
- Strong applied data science skills - ability to recognize data patterns, understand how and when to use various machine learning approaches (eg. supervised/unsupervised learning, deep learning etc.), and evaluate the performance of ML algorithms.
- Proven ability to remain up-to-date with the latest advancements in Generative AI approaches (eg. OpenAI, LangChain, Stable Diffusion APIs).
- Experience developing, documenting, and supporting REST APIs
- A degree in Computer Science, Engineering, or a related field or equivalent practical experience.
Get to Know Us:
At Smartsheet, your ideas are heard, your potential is supported, and your contributions have real impact. You’ll have the freedom to explore, push boundaries, and grow beyond your role. We welcome diverse perspectives and nontraditional paths—because we know that impact comes from individuals who care deeply and challenge thoughtfully. When you’re doing work that stretches you, excites you, and connects you to something bigger, that’s magic at work. Let’s build what’s next, together.
Equal Opportunity Employer:
Smartsheet is an Equal Opportunity (EEO) employer committed to fostering an inclusive environment with the best employees. It is our policy to provide equal employment opportunities to all qualified applicants in accordance with applicable laws in the US, UK, Australia, Germany, Costa Rica, Japan, Bulgaria, and India. All qualified applicants will receive consideration without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, protected veteran or disabled status, or genetic information.
If there are preparations we can make to help ensure you have a comfortable and positive interview experience, please let us know.
#LI-Remote
Ready to apply?
Apply to Smartsheet
Principal Data Engineer / Architect - Individual Contributor
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For over 20 years, Smartsheet has helped people and teams achieve–well, anything. From seamless work management to smart, scalable solutions, we’ve always worked with flow. We’re building tools that empower teams to automate the manual, uncover insights, and scale smarter. But more than that, we’re creating space– space to think big, take action, and unlock the kind of work that truly matters. Because when challenge meets purpose, and passion turns into progress, that’s magic at work, and it’s what we show up for everyday.
Our India Global Capability Center isn't just supporting global operations—we’re leading global innovation. After scaling rapidly into a best-in-class hub, we deliver the product innovation and enterprise capabilities that accelerate our global growth, profitability, and scale. As we expand Smartsheet India, we’re searching for Principal Data & AI/ML Ops Engineers, who crave variety and ownership. You’ll have the opportunity to work across multiple teams and disciplines, building a versatile skillset while solving the complex challenges of a global platform.
You Will:
- Data Architecture and Design: Designing and overseeing the architecture of scalable and reliable data platforms, including data pipelines, storage solutions, and processing systems
- Data Modelling and Management:Developing and implementing data models, ensuring data quality, and establishing data governance policies
- Data Pipeline Development: Building and optimising data pipelines for ingesting, processing, and transforming large datasets from various sources
- Performance Optimisation: Identifying and resolving performance bottlenecks in data pipelines and systems, ensuring efficient data retrieval and processing
- Technology Evaluation and Innovation: Staying abreast of emerging data technologies and exploring opportunities for innovation to improve the organisation’s data infrastructure
- Troubleshooting and Problem Solving: Diagnosing and resolving complex data-related issues, ensuring the stability and reliability of the data platform
- Data Security and Compliance: Implementing data security measures, ensuring compliance with data governance policies, and protecting sensitive data
- Perform other duties as assigned
You Have:
- Enterprise SaaS software solutions with high availability and scalability
- Solution handling large scale structured and unstructured data from varied data sources
- Experience in building and maintaining data platform systems such as distributed compute, data orchestration, distributed storage, streaming infrastructure ensuring scalability, reliability, efficiency and security
- Working with Product engineering team to influence designs with data, AI and analytics use cases in mind
- In depth experience in System design involving large Petabytes of data with Databricks Lakehouse
- Experience in modern AI/Data infrastructure patterns, Semantics layer Organizing data for AI agents (metadata, context)
- AI/MLOps workflows on Databricks , MLFlow, Mosaic AI Agent Framework, Unity Catalog, Vector Search, Knowledge Graph
- Knowledge of AI/ML frameworks like LangChain, LangGraph for AI/ML Ops pipeline integration
- Cloud Platforms: Hands-on experience with at least one major cloud provider (AWS, Azure, or GCP). Experience in AWS hosted data platform is preferable
- Programming languages like Python, SQL, and potentially Java or Scala
- Exposure to Snowflake and Data pipeline frameworks like Airbyte/Airflow is preferable
- Modern software engineering practices like Kubernetes, CI/CD, IAC tools (Preferably Terraform), Observability, monitoring and alerting
- Solution Cost Optimisations and design to cost
- Driving engineering excellence initiatives
- Legally eligible to work in India on an ongoing basis
Get to Know Us:
At Smartsheet, your ideas are heard, your potential is supported, and your contributions have real impact. You’ll have the freedom to explore, push boundaries, and grow beyond your role. We welcome diverse perspectives and nontraditional paths—because we know that impact comes from individuals who care deeply and challenge thoughtfully. When you’re doing work that stretches you, excites you, and connects you to something bigger, that’s magic at work. Let’s build what’s next, together.
Equal Opportunity Employer:
Smartsheet is an Equal Opportunity (EEO) employer committed to fostering an inclusive environment with the best employees. It is our policy to provide equal employment opportunities to all qualified applicants in accordance with applicable laws in the US, UK, Australia, Germany, Costa Rica, Japan, Bulgaria, and India. All qualified applicants will receive consideration without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, protected veteran or disabled status, or genetic information.
If there are preparations we can make to help ensure you have a comfortable and positive interview experience, please let us know.
#LI-Remote
Ready to apply?
Apply to Smartsheet
As a Staff Data Scientist, you will act as a senior technical leader and trusted advisor across multiple teams. You’ll guide stakeholders through the complexity of modern AI systems, with a particular focus on agentic AI architectures (including LangGraph, LangFuse, and related tooling), as well as broader machine‑learning strategy. This role blends deep technical expertise, consultative problem‑solving, and cross‑functional leadership.
You will often support several initiatives simultaneously, helping teams understand feasibility, scope, and risk while shaping high‑impact AI solutions that align with business needs. You’ll also mentor junior colleagues, elevate data‑science practices, and contribute hands‑on to the development of production‑grade AI systems.
What you'll do:
AI Consulting & Advisory
- Partner with product, engineering, and business teams to translate ambiguous problems into clear AI opportunities.
- Provide expert guidance on agentic AI, including workflow orchestration, evaluation, observability, and safety.
- Assess the complexity, feasibility, and expected value of proposed AI initiatives, helping teams prioritise effectively.
- Communicate trade‑offs, risks, and solution paths to both technical and non‑technical audiences.
AI & ML Solution Design
- Architect end‑to‑end AI systems that solve real business problems, from early discovery through deployment.
- Design agent‑based workflows, retrieval‑augmented pipelines, and ML‑powered automation.
- Define evaluation strategies, data requirements, and success metrics for AI features and products.
- Collaborate with engineering teams to ensure solutions are scalable, maintainable, and aligned with platform strategy.
Hands‑On Technical Work
- Build prototypes, proof‑of‑concepts, and production‑ready components using Python, modern AI frameworks, and cloud tooling.
- Develop and refine agentic AI workflows using LangGraph, LangChain, LangFuse, or similar frameworks.
- Implement machine‑learning models, retrieval systems, and data pipelines where needed.
- Contribute to internal libraries, tooling, and best practices for AI development.
Leadership & Mentorship
- Mentor junior and mid‑level data scientists, providing guidance on modelling, experimentation, and system design.
- Lead technical discussions, design reviews, and cross‑team collaboration sessions.
- Champion high standards for code quality, documentation, and reproducibility.
- Help shape the long‑term AI strategy and technical roadmap, through your technical knowledge on the art of the possible, and the business problems our clients face.
What you'll bring:
- Extensive experience in data science, machine learning, or applied AI, including hands‑on coding in Python and common data science libraries, such as Numpy, Scipy, Pandas, SKlearn, Spacy.
- Ability with prototyping frameworks such as Dash.
- Good working understanding of code version control with Git.
- Experience with big data tools, such as: Spark, Dask, or alternatives.
- Strong understanding of agentic AI, orchestration frameworks, and LLM‑based system design.
- Ability to evaluate project complexity, identify risks, and guide teams toward pragmatic solutions.
- Experience designing and delivering AI systems in production environments.
- Excellent communication skills and the ability to influence beyond your immediate team.
- Great mentoring skills.
- Comfort working across multiple projects and shifting priorities.
Nice to Have
- Experience with observability and evaluation tools such as LangFuse, Weights & Biases, or similar.
- Familiarity with agentic evals and prompt‑engineering patterns.
- Background in consulting, technical advisory, or cross‑functional leadership roles.
- Experience with cloud platforms (AWS, GCP, Azure) and modern MLOps practices.
Ready to apply?
Apply to Cision
AI/ML Engineer II
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Position Summary:
Precision AQ’s Product Solutions team is expanding its AI and machine learning engineering capabilities in India. This role is responsible for designing, developing, deploying, and scaling production-grade AI/ML solutions that directly support Precision AQ products and productized services across oncology access, analytics, and AI-enabled offerings.
The AI/ML Engineer operates as a hands-on technical contributor, working closely with product management, engineering, data science, and research teams to translate business problems into robust, scalable AI systems. The role spans model development, optimization, deployment, and operationalization, with a strong emphasis on Generative AI, Large Language Models (LLMs), and applied machine learning in real-world production environments.
The successful candidate is technically rigorous, execution-oriented, and comfortable operating in fast-paced, multi-product environments with evolving requirements.
Essential functions of the job include but are not limited to: (This is NOT meant to be an exhaustive task list)
- AI / ML Model Development & Optimization
- Design, develop, fine-tune, and evaluate machine learning, deep learning, and Generative AI models, including Large Language Models (LLMs).
- Apply appropriate modeling techniques (supervised, unsupervised, NLP, deep learning) based on problem context and data constraints.
- Optimize model performance across accuracy, latency, scalability, and cost dimensions.
- Conduct rigorous model evaluation, validation, and benchmarking using large-scale datasets.
- Apply data preprocessing, feature engineering, augmentation, and synthetic data generation techniques to improve model robustness.
- Production Deployment & MLOps
- Design and implement scalable, production-ready AI solutions integrated into existing platforms and workflows.
- Build, maintain, and improve MLOps pipelines for model training, deployment, monitoring, and lifecycle management.
- Deploy and manage AI applications in cloud environments (Azure, AWS, or GCP), including containerization and orchestration where applicable.
- Monitor model performance in production; identify drift, degradation, or failures and implement remediation strategies.
- Troubleshoot and resolve AI/ML engineering issues across development and production environments.
- Cross-Functional Collaboration & Integration
- Partner with Product Managers, Product Owners, Software Engineers, Data Scientists, and Research teams to align AI solutions with business and product objectives.
- Translate product requirements and use cases into technical architectures and model designs.
- Support integration of AI capabilities into customer-facing products and internal platforms.
- Communicate technical concepts, tradeoffs, and limitations clearly to non-technical stakeholders.
- Data & Domain Application
- Work with structured and unstructured datasets, including healthcare, claims, and life sciences data, to build high-performance AI systems.
- Ensure responsible handling, transformation, and validation of data used for model training and inference.
- Collaborate with data engineering and QA teams to ensure data pipelines and AI workflows are production-ready and auditable.
- Technical Excellence & Continuous Improvement
- Stay current with advances in Generative AI, LLM architectures, model fine-tuning techniques, and applied machine learning.
- Contribute to internal best practices, standards, and reusable components for AI/ML development.
- Document AI/ML workflows, architectures, methodologies, and lessons learned for internal knowledge sharing.
- Proactively identify opportunities to improve scalability, reliability, and efficiency of existing AI systems.
Qualifications:
BA Degree in Computer Science, Software Engineering, Operations Engineering, Business Management or other related field
Minimum Required:
- Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related quantitative field.
- Minimum 3+ years of hands-on experience in an AI/ML or data science role delivering production-deployed solutions.
- Strong proficiency in Python and SQL; experience building scalable ML/NLP workflows.
- Deep hands-on experience with machine learning, deep learning, and natural language processing.
- Experience working with Generative AI and Large Language Models, including fine-tuning and evaluation techniques.
- Working knowledge of data preprocessing, feature engineering, and model validation practices.
- Experience deploying AI solutions in cloud environments (Azure, AWS, or GCP).
- Familiarity with containerization and orchestration tools (e.g., Docker, Kubernetes).
Preferred:
- Experience building AI solutions in healthcare, life sciences, analytics, or regulated data
- Hands-on experience with MLOps frameworks and monitoring strategies.
- Experience integrating AI models into SaaS products or productized services.
- Familiarity with distributed systems, APIs, and modern software engineering practices.
- Exposure to enterprise AI governance, security, or compliance considerations.
Competencies:
- Communication Skills: Written, Verbal, and Presentation: The successful candidate must have the ability to read, analyze, and interpret production data, financial reports, and legal documents. Excellent verbal, written, presentation, interpersonal skills including ability to clearly respond to common inquiries or complaints from customers, employees, and members of the business community. Must possess a rapid agility to reply to emails, provide instructions of work stream necessities or issues encountered, business and report writings in a succinct and informative manner.
- Business Judgment and Strategic Thinking: Ability to think, act, and deliver value in the best interest of our clients with respect to common practices of the healthcare consulting field. Ability to extrapolate from the specific to the general and interpret from the general to the specific.
- Analytic Skills: Framing macro problems into action steps or work plans for resolutions. Structuring a persuasive client presentation based on in-depth or expansive excel spreadsheets. Demonstrable interpretive and solution identification skills with the ability to understand multiple types of quantitative and qualitative data heightened with strong resolution skills.
- Collaboration and Teamwork: Ability to give and receive constructive feedback and work effectively across the organization to accomplish team goals is critical. The successful candidate must possess excellent judgment, management, and conflict resolution skills. Ability to work with team members to convey results, incorporate enhancements and productionize processes across projects. Must be able to understand the dynamics of how a team interconnects and relies upon every member.
- Strategic Thinking: Conceptualize outside of the aspects of a project at hand, with an ability to visualize how the work contributes to and drives forward the overall project.
- Solutions oriented: must be able to display resourcefulness and confidence under pressure
- Resilience: must be able to look past obstacles and roadblocks, ask questions and for support, and find their way around any obstacle.
Any data provided as a part of this application will be stored in accordance with our Privacy Policy. For CA applicants, please also refer to our CA Privacy Notice.
Precision Medicine Group is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, age, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status or other characteristics protected by law.
If you are an individual with a disability and require a reasonable accommodation to complete any part of the application process or are limited in the ability or unable to access or use this online application process and need an alternative method for applying, you may contact Precision Medicine Group at QuestionForHR@precisionmedicinegrp.com.
It has come to our attention that some individuals or organizations are reaching out to job seekers and posing as potential employers presenting enticing employment offers. We want to emphasize that these offers are not associated with our company and may be fraudulent in nature. Please note that our organization will not extend a job offer without prior communication with our recruiting team, hiring managers and a formal interview process.
Ready to apply?
Apply to Precision Medicine Group
AI/ML Engineer II
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Position Summary:
Precision AQ’s Product Solutions team is expanding its AI and machine learning engineering capabilities in India. This role is responsible for designing, developing, deploying, and scaling production-grade AI/ML solutions that directly support Precision AQ products and productized services across oncology access, analytics, and AI-enabled offerings.
The AI/ML Engineer operates as a hands-on technical contributor, working closely with product management, engineering, data science, and research teams to translate business problems into robust, scalable AI systems. The role spans model development, optimization, deployment, and operationalization, with a strong emphasis on Generative AI, Large Language Models (LLMs), and applied machine learning in real-world production environments.
The successful candidate is technically rigorous, execution-oriented, and comfortable operating in fast-paced, multi-product environments with evolving requirements.
Essential functions of the job include but are not limited to: (This is NOT meant to be an exhaustive task list)
- AI / ML Model Development & Optimization
- Design, develop, fine-tune, and evaluate machine learning, deep learning, and Generative AI models, including Large Language Models (LLMs).
- Apply appropriate modeling techniques (supervised, unsupervised, NLP, deep learning) based on problem context and data constraints.
- Optimize model performance across accuracy, latency, scalability, and cost dimensions.
- Conduct rigorous model evaluation, validation, and benchmarking using large-scale datasets.
- Apply data preprocessing, feature engineering, augmentation, and synthetic data generation techniques to improve model robustness.
- Production Deployment & MLOps
- Design and implement scalable, production-ready AI solutions integrated into existing platforms and workflows.
- Build, maintain, and improve MLOps pipelines for model training, deployment, monitoring, and lifecycle management.
- Deploy and manage AI applications in cloud environments (Azure, AWS, or GCP), including containerization and orchestration where applicable.
- Monitor model performance in production; identify drift, degradation, or failures and implement remediation strategies.
- Troubleshoot and resolve AI/ML engineering issues across development and production environments.
- Cross-Functional Collaboration & Integration
- Partner with Product Managers, Product Owners, Software Engineers, Data Scientists, and Research teams to align AI solutions with business and product objectives.
- Translate product requirements and use cases into technical architectures and model designs.
- Support integration of AI capabilities into customer-facing products and internal platforms.
- Communicate technical concepts, tradeoffs, and limitations clearly to non-technical stakeholders.
- Data & Domain Application
- Work with structured and unstructured datasets, including healthcare, claims, and life sciences data, to build high-performance AI systems.
- Ensure responsible handling, transformation, and validation of data used for model training and inference.
- Collaborate with data engineering and QA teams to ensure data pipelines and AI workflows are production-ready and auditable.
- Technical Excellence & Continuous Improvement
- Stay current with advances in Generative AI, LLM architectures, model fine-tuning techniques, and applied machine learning.
- Contribute to internal best practices, standards, and reusable components for AI/ML development.
- Document AI/ML workflows, architectures, methodologies, and lessons learned for internal knowledge sharing.
- Proactively identify opportunities to improve scalability, reliability, and efficiency of existing AI systems.
Qualifications:
BA Degree in Computer Science, Software Engineering, Operations Engineering, Business Management or other related field
Minimum Required:
- Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related quantitative field.
- Minimum 3+ years of hands-on experience in an AI/ML or data science role delivering production-deployed solutions.
- Strong proficiency in Python and SQL; experience building scalable ML/NLP workflows.
- Deep hands-on experience with machine learning, deep learning, and natural language processing.
- Experience working with Generative AI and Large Language Models, including fine-tuning and evaluation techniques.
- Working knowledge of data preprocessing, feature engineering, and model validation practices.
- Experience deploying AI solutions in cloud environments (Azure, AWS, or GCP).
- Familiarity with containerization and orchestration tools (e.g., Docker, Kubernetes).
Preferred:
- Experience building AI solutions in healthcare, life sciences, analytics, or regulated data
- Hands-on experience with MLOps frameworks and monitoring strategies.
- Experience integrating AI models into SaaS products or productized services.
- Familiarity with distributed systems, APIs, and modern software engineering practices.
- Exposure to enterprise AI governance, security, or compliance considerations.
Competencies:
- Communication Skills: Written, Verbal, and Presentation: The successful candidate must have the ability to read, analyze, and interpret production data, financial reports, and legal documents. Excellent verbal, written, presentation, interpersonal skills including ability to clearly respond to common inquiries or complaints from customers, employees, and members of the business community. Must possess a rapid agility to reply to emails, provide instructions of work stream necessities or issues encountered, business and report writings in a succinct and informative manner.
- Business Judgment and Strategic Thinking: Ability to think, act, and deliver value in the best interest of our clients with respect to common practices of the healthcare consulting field. Ability to extrapolate from the specific to the general and interpret from the general to the specific.
- Analytic Skills: Framing macro problems into action steps or work plans for resolutions. Structuring a persuasive client presentation based on in-depth or expansive excel spreadsheets. Demonstrable interpretive and solution identification skills with the ability to understand multiple types of quantitative and qualitative data heightened with strong resolution skills.
- Collaboration and Teamwork: Ability to give and receive constructive feedback and work effectively across the organization to accomplish team goals is critical. The successful candidate must possess excellent judgment, management, and conflict resolution skills. Ability to work with team members to convey results, incorporate enhancements and productionize processes across projects. Must be able to understand the dynamics of how a team interconnects and relies upon every member.
- Strategic Thinking: Conceptualize outside of the aspects of a project at hand, with an ability to visualize how the work contributes to and drives forward the overall project.
- Solutions oriented: must be able to display resourcefulness and confidence under pressure
- Resilience: must be able to look past obstacles and roadblocks, ask questions and for support, and find their way around any obstacle.
Any data provided as a part of this application will be stored in accordance with our Privacy Policy. For CA applicants, please also refer to our CA Privacy Notice.
Precision Medicine Group is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, age, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status or other characteristics protected by law.
If you are an individual with a disability and require a reasonable accommodation to complete any part of the application process or are limited in the ability or unable to access or use this online application process and need an alternative method for applying, you may contact Precision Medicine Group at QuestionForHR@precisionmedicinegrp.com.
It has come to our attention that some individuals or organizations are reaching out to job seekers and posing as potential employers presenting enticing employment offers. We want to emphasize that these offers are not associated with our company and may be fraudulent in nature. Please note that our organization will not extend a job offer without prior communication with our recruiting team, hiring managers and a formal interview process.
Ready to apply?
Apply to Precision AQ
About Manifest Global
Manifest Global is building the infrastructure for global human capital mobility -connecting students, schools, universities, and employers across 50+ countries. Our portfolio spans Cialfo (AI-powered college counseling, 2,000+ schools), BridgeU (university guidance for international schools globally), Kaaiser (trusted study abroad counseling across India and Southeast Asia), and Explore (AI-powered university outreach, 1,000+ university partners). Together, we move talent across borders at scale. $80M raised. Still early.
About This Role
Manifest Global operates four brands across 50+ countries, generating data across thousands of schools, hundreds of thousands of students, and 1,000+ university partners. Counselor behaviour, student application journeys, university conversion rates, placement outcomes, attribution revenue - it's all there. The data exists. The question is whether the infrastructure around it is good enough to make it useful.
Right now, the data platform works. Pipelines run, the warehouse holds data, the BI layer surfaces reports. But Manifest is growing - new brands, new markets, new activation use cases - and the infrastructure needs to scale with it. There are pipelines that need to be more reliable. Transformation logic that needs to be cleaner. Warehouse design that needs to handle more volume without degrading performance. And an activation layer - reverse ETL, operational analytics, data flowing into the tools the business actually uses - that is still being built.
As a Senior Data Engineer, you will own significant parts of the data platform end to end - ingestion, transformation, warehouse, activation - and you will be one of the people who determines whether Manifest's data infrastructure is a genuine competitive advantage or a persistent constraint. You will work closely with Principal Engineers, Product, and business stakeholders across all four brands, and you will be expected to operate with the ownership and judgment of someone who has built production-grade data systems before.
What makes this role different: Manifest has real data - cross-brand, multi-geography, commercially significant data. The stack is modern: Snowflake, dbt, Hevo, Airtable, Metabase. The problems are real. And when the data infrastructure surfaces the right insight, it changes a decision that affects real students and real institutions.
AI is central to how we build: This isn't just a data engineering role - it is a role where you will actively design and build AI infrastructure that accelerates the team's own development velocity. We use Snowflake Cortex AI with Claude in our daily engineering workflow - for debugging, RCA, query optimisation, and pipeline analysis. We have already cut root cause analysis time. The next step is embedding AI deeper: automated ticket handling, intelligent monitoring, and AI-assisted development tooling that lets the team move faster without sacrificing reliability.
What You Will Own
1. AI Infrastructure for Data Engineering
- Design and build AI-assisted development tooling - LLM-powered code generation for dbt models, SQL transformations, and pipeline scaffolding that dramatically reduces time-to-production for new data assets
- Build intelligent data quality and anomaly detection systems - AI-driven monitoring that learns normal patterns across pipelines and surfaces anomalies before they propagate downstream, replacing manual threshold-based alerting
- Implement AI-augmented data cataloguing and lineage - automated documentation generation, schema understanding, and semantic tagging so engineers spend less time writing docs and more time building
- Develop AI-powered pipeline debugging and root cause analysis - tooling that diagnoses failures, traces impact through the DAG, and proposes fixes rather than requiring engineers to trace failures manually
- Build and maintain the infrastructure that supports AI features - vector stores, embedding pipelines, retrieval layers, and model serving infrastructure that powers AI capabilities across Cialfo, BridgeU, and Explore
- Evaluate and adopt emerging AI developer tools - stay ahead of how AI tooling (Claude, Cortex AI, GitHub Copilot, LLM APIs) can be embedded into the team's workflow to shorten feedback loops and accelerate feature delivery
2. Data Warehouse Design, Cost & Maintenance
- Own significant portions of the Snowflake data warehouse - schema design, performance optimisation, and the integrity of the data models that the rest of the stack depends on
- Apply strong data warehousing methodologies: dimensional modelling, layered transformation logic, clear separation between raw, staged, and served layers
- Design and build cross-brand data primitives - shared, canonical data layers for K12, Student, University, and Application data that work consistently across Cialfo, BridgeU, and Kaaiser. This is active work and a critical foundation for the multi-brand data platform
- Own Snowflake cost optimisation - monitor warehouse spend, identify high-cost queries and sync jobs, right-size warehouse configurations, and drive measurable reductions in monthly compute spend.
- Ensure the warehouse handles increasing data volumes from across all four brands without degrading query performance or downstream reliability
3. ETL/ELT Pipelines, Scheduling & Transformation Logic
- Design, build, and maintain production-grade data pipelines - ingestion via Hevo or similar, transformation via dbt, SQL-based logic that is clean, documented, and maintainable
- Design and manage Snowflake Task DAGs - build and maintain dependency-chained task graphs for ingestion, LLM processing, and sync workflows. Understand how to structure root tasks, child tasks, CRON scheduling, warehouse assignment, and failure isolation so pipelines don't cascade-fail
- Own Airtable as an operational data layer - manage Snowflake-to-Airtable and Airtable-to-Snowflake sync workflows, including the
SNOWFLAKE_TO_AIRTABLE_TABLELISTsync config, upsert logic, incremental filters, and sync cost optimisation. Airtable is both a key data source and a reporting destination across brands - Build and own reverse ETL workflows that activate warehouse data into operational tools - getting the right data into the hands of the teams that need it, not just into dashboards
- Take full ownership of pipeline failures: root cause identification, fix, downstream impact analysis, and prevention - not just resolution
4. Data Quality & Reliability
- Define and enforce data quality standards across datasets you own - automated validations, delta checks, row counts, time-based monitoring
- Build monitoring and alerting that surfaces problems before they reach the business
- Document data lineage, transformation assumptions, and technical decisions so the platform is understandable and maintainable as the team grows
5. BI Platform & Reporting
- Maintain and enhance the existing BI layer - Metabase and build reporting interfaces that non-technical stakeholders can actually use
- Collaborate with Product and Analytics teams to translate business needs into reliable technical solutions
- Communicate clearly across all four brands - be the person who can explain a data problem in business terms and a business problem in data terms
What Success Looks Like
You'll start by building a complete picture of the current state - which pipelines are fragile, where data quality is inconsistent, what the highest-impact improvements look like, and where activation use cases aren't yet built. You will have a point of view on where to move first.
From there, the infrastructure will be measurably more reliable. Pipelines that were breaking will run consistently. Data quality issues will be caught early or prevented entirely. The BI layer will be getting used - not just maintained.
Over time, the data platform will be something the business genuinely relies on - fast enough to support the pace of growth, reliable enough that data consumers trust what they are looking at, and built in a way that the next engineer who joins can understand and extend without starting from scratch.
About You
Qualifications
- Bachelor's degree in Computer Science, Engineering, or a related field - or equivalent practical experience
Experience
- 5+ years building and maintaining production-grade data pipelines and data warehouses - not prototypes, but systems that real business decisions depend on
- Strong experience architecting and implementing large-scale business intelligence solutions
- Strong experience in data warehouse design and advanced SQL
- Hands-on experience with the modern data stack: Snowflake (or equivalent cloud warehouse), dbt, Hevo or Airbyte or similar
- Advanced SQL proficiency: CTEs, window functions,
QUALIFY, query optimisation, and understanding the difference between SQL that works and SQL that scales - Experience with Snowflake-native features: Task DAGs, Dynamic Tables, Snowflake Cortex AI,
AI_COMPLETE, warehouse sizing, and query profiling - Experience with Airtable as an operational data layer - syncing data between Snowflake and Airtable, managing upsert logic, and keeping sync costs low
- Experience owning Snowflake cost monitoring and optimisation - identifying expensive queries, bloated sync jobs, and warehouse over-provisioning
- Experience with user-facing BI tools: Metabase, Looker, or similar
- Experience working in agile, ticket-based workflows (Jira)
- Experience building or integrating AI/LLM tooling into data engineering workflows - specifically Snowflake Cortex AI, or LLM APIs (OpenAI, Anthropic, etc.) for structured data tasks, fuzzy matching, or pipeline automation
- Familiarity with vector databases, embedding pipelines, or retrieval-augmented generation (RAG) infrastructure is a strong plus
- Exposure to MLOps or AI infrastructure patterns - model serving, feature stores, or AI monitoring - is an advantage
Skills & Qualities
- You take ownership of reliability. When a pipeline fails, you don't just fix the immediate problem - you understand why it happened, what it affected downstream, and what needs to change so it doesn't happen again
- You communicate clearly with non-technical stakeholders. You've sat in a requirements conversation with a commercial or product team, understood what they were actually asking for, and built something that answered the real question
- You document your work well enough that someone else could maintain it - data lineage, transformation assumptions, technical decisions
- Comfortable working in a multi-brand, multi-stakeholder environment where data problems span different systems, teams, and geographies
- Strong problem-solving skills and attention to detail
- Ability to hold multiple priorities simultaneously and make good judgments about what to work on first
- You're genuinely excited about AI as a force multiplier for engineering teams - you actively use AI tools in your own workflow and have a point of view on how they can make data teams faster without sacrificing reliability
Why Manifest
We're building the infrastructure for global human capital mobility - the rails that move students, schools, universities, and employers across 50+ countries. Cialfo is in 2,000+ schools. Explore is trusted by 1,000+ universities. BridgeU runs across the UK, Europe, and the Middle East. Kaaiser has guided students across India and Southeast Asia since 1997.
The opportunity is real. $700B flows annually in remittances from migrant workers. 85M workers will be missing from developed economies by 2030. We're building the operating system that changes that.
$80M raised from Tiger Global, SIG, and Square Peg. Still early.
The team has already built the infrastructure for AI-native engineering - shared conventions, a live skills library, AI-assisted workflows across engineering, QE, product, and design. Saige is in production. Explore's AI capabilities are in production. This isn't an aspiration we're hiring you to bring to life. It's an operating system we're hiring you to extend, scale, and make permanent.
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Senior Staff Software Engineer ( Machine learning Platform)
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About Tekion:
Positively disrupting an industry that has not seen any innovation in over 50 years, Tekion has challenged the paradigm with the first and fastest cloud-native automotive platform that includes the revolutionary Automotive Retail Cloud (ARC) for retailers, Automotive Enterprise Cloud (AEC) for manufacturers and other large automotive enterprises and Automotive Partner Cloud (APC) for technology and industry partners. Tekion connects the entire spectrum of the automotive retail ecosystem through one seamless platform. The transformative platform uses cutting-edge technology, big data, machine learning, and AI to seamlessly bring together OEMs, retailers/dealers and consumers. With its highly configurable integration and greater customer engagement capabilities, Tekion is enabling the best automotive retail experiences ever. Tekion employs close to 3,000 people across North America, Asia and Europe.
Why This Role Matters
This role powers Tekion’s AI‑native, end‑to‑end automotive platform by turning unified dealership data across DMS, CRM, Digital Retail, Service, and Payments into real‑time intelligence. You’ll operationalize a graph‑based contextual ecosystem so agents can retrieve the right context, enforce policy, and personalize experiences that drive measurable dealer outcomes. You’ll also build the resilient control layer - MCP and the LLM Gateway - that enables safe, cost‑efficient, multi‑provider LLM usage. Finally, you’ll define the standards for building, evaluating, deploying, and governing agentic systems so product teams can ship AI features quickly, safely, and at scale. In addition to enabling agentic systems powered by LLMs, this role also drives building the platform for classical ML models driving optimization across dealership operations.
What Makes This Opportunity Unique
This role offers direct, measurable impact on dealer outcomes and consumer experiences across Tekion’s Automotive Retail Cloud and Automotive Enterprise Cloud, with end‑to‑end ownership of an LLM control plane and gateway that serve multi‑tenant workloads under SLAs and, quality and cost guardrails. You’ll leverage a rich vertical dataset and domain graph spanning sales, service, parts, F&I, accounting, and consumer touchpoints to power context‑aware agents and retrieval‑augmented generation. You’ll also shape core levers - agent orchestration patterns, evaluation frameworks, and safety guardrails - so improvements in latency, reliability, evaluation quality, and safety translate into dealer KPIs like upsell, cycle time, CSAT, and service revenue. You’ll also maintain and enhance the platform to support classical supervised and unsupervised ML models .
Responsibilities
- Build and run the LLM control plane/gateway: smart routing, rate limits/quotas, failover, and token/cost tracking.
- Ship a unified API and SDKs (REST/gRPC) with normalized schemas, structured outputs, caching, and full observability (traces/logs/metrics).
- Enforce safety and privacy by default: content filtering, prompt/response validation, and PII redaction.
- Enable multi‑model, multi‑vendor use LLMs with automated canarying and versioning.
- Own the agent runtime: tool registry, permissions, function calling, grounding, and retrieval.
- Design orchestration patterns (sequential, planner‑executor, streaming) and manage agent state and long‑running workflows.
- Enabling platform components for training and scoring pipelines for classical ML (e.g., XGBoost/LightGBM/linear/trees) and deep models; standardize experiment tracking and packaging.
- Create components to Monitor model and data drift, retraining and tuning models as needed to maintain accuracy and relevance.
- Add human‑in‑the‑loop review and safe‑actioning before agents touch dealer systems.
- Evolve the domain graph and entity resolution; build reliable data ingestion pipelines.
- Serve real‑time context to agents (profiles, inventory, pricing, appointments, service history) with access controls and lineage.
- Power retrieval with hybrid search (graph + vector + keyword) and smart cache/TTL to balance accuracy, latency, and cost.
- Run continuous offline/online evaluations for quality, factuality, bias, and safety for the platform sanity.
- Define SLOs for latency (p50/p95), uptime, and cost view capabilities; enable autoscaling and spend controls.
- Maintain a model/agent registry, versioning, approvals, audit trails, and reproducibility; support compliances where needed.
- Provide templates/CLIs, sandboxes, and docs so product teams can build and ship fast; mentor engineers and champion MLOps and AI safety best practices.
Desired Skills & Experience
- 12–15+ years building large‑scale data/ML or platform systems; strong software engineering fundamentals (Abstracted API design, concurrency, distributed systems).
- Production experience with Python plus one of Java/Scala/Go; microservices and API design.
- MLOps at scale: pipelines (Airflow/Kubeflow), tracking/registry (MLflow), CI/CD for models, A/B testing, shadow/canary, and online feature computation (Spark/Flink/Kafka).
- Cloud and containers: AWS (preferred), plus Docker/Kubernetes; performance, reliability, and cost engineering in multi‑tenant SaaS.
- Practical ML knowledge (feature engineering, training, evaluation, drift detection); experience deploying models that power user‑facing workflows.
- Built or operated an LLM gateway/control plane: provider adapters, routing/policies, caching, quota/rate‑limit, cost and token accounting.
- Agentic systems: tool use/function calling, orchestration frameworks, human‑in‑the‑loop, safety/guardrails, and online evaluation/telemetry.
- Graph and retrieval: knowledge graphs (e.g., Neo4j/Neptune/TigerGraph), GraphQL, vector search (e.g., pgvector/Qdrant/Milvus), hybrid retrieval patterns.
Preferred Mindset
- Platform‑as‑product: obsess over developer experience, paved roads, and clear SLAs.
- Thinks in systems - observability, fallback, access control are core, not afterthoughts.
- Passionate about AI - enjoys enabling real-world LLM and agentic use cases.
- Cost‑aware builder: you treat latency and dollars as first‑class metrics and design for graceful degradation.
- Vendor‑agnostic thinker: choose the right model/provider per use case; build for portability and resilience.
- Documentation and teaching: you make complex systems understandable; you uplevel teams.
Tekion is proud to be an Equal Employment Opportunity employer. We do not discriminate based upon race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, victim of violence or having a family member who is a victim of violence, the intersectionality of two or more protected categories, or other applicable legally protected characteristics.
For more information on our privacy practices, please refer to our Applicant Privacy Notice here.
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Manager, Machine Learning & Data Science
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Opportunity Overview
As the Manager, Machine Learning & Data Science, you will play a key role in building and scaling Cohere Health’s AI capabilities in India. You’ll lead a team of machine learning engineers and data scientists focused on developing and deploying models that automate and augment complex clinical and administrative workflows.
This team is responsible for the full lifecycle of applied machine learning and data science—from problem framing and experimentation to production model deployment and ongoing optimization. You’ll work with structured and unstructured healthcare data to generate insights and power intelligent systems that improve prior authorization and broader clinical decision-making.
As a player-coach, you’ll combine hands-on technical contributions with team leadership, helping to establish best practices, mentor team members, and drive high-impact solutions in close partnership with Product, Engineering, Clinical, and Analytics stakeholders. This is an opportunity to shape both the technical direction and team culture within a growing global organization.
What you’ll do:
- Lead, mentor, and develop a team of machine learning engineers and data scientists, fostering a collaborative, high-performance environment
- Act as a hands-on contributor across the ML/DS lifecycle, including data exploration, feature engineering, model development, evaluation, and deployment
- Design, develop, and deploy machine learning models for retrieval, classification, and generative use cases across structured and unstructured data
- Translate complex business and clinical problems into scalable machine learning and data science solutions
- Establish and uphold best practices for experimentation, model validation, performance tracking, and reproducibility
- Partner cross-functionally with Product, Engineering, Clinical, and Analytics teams to align solutions with business priorities
- Guide the development of scalable data science and machine learning systems, including data preprocessing pipelines and production workflows
- Monitor model performance, identify opportunities for improvement, and drive continuous iteration and optimization
- Communicate technical concepts, methodologies, and insights clearly to both technical and non-technical stakeholders
- Contribute to hiring and scaling the team in India, including recruiting, onboarding, and coaching team members
What you’ll need:
Must-haves
- Minimum 8+ years of experience in machine learning, data science, or applied AI roles, of those a minimum 2+ years of experience must be leading technical teams
- Strong hands-on experience building, evaluating, and deploying machine learning models in production
- Solid foundation in statistical methods, experimental design, and model evaluation
- Proficiency in Python and experience with ML frameworks (e.g., PyTorch, scikit-learn)
- Experience working with large, complex datasets (structured and/or unstructured)
- Strong problem-solving skills with the ability to translate business challenges into analytical solutions
- Excellent communication skills, with the ability to present complex concepts clearly to diverse stakeholders
- Experience working in fast-paced, evolving environments
Nice-to-haves
- Experience in healthcare, particularly with payer, provider, or clinical data
- Experience with NLP, deep learning (e.g., transformers), or generative AI (e.g., RAG)
- Familiarity with MLOps practices and production ML systems
- Experience with Spark or large-scale data processing frameworks
- Exposure to cloud platforms (e.g., AWS, SageMaker)
- Experience working in a global or distributed team environment
- Prior experience in a GCC or building teams in India
Interview Process*:
- Connect with Talent Acquisition
- Meet with the Hiring Manager
- Behavioral Interview(s)
- Case Study
- Interview with Senior Leadership
*Subject to change
About Cohere Health:
Cohere Health’s clinical intelligence platform delivers AI-powered solutions that streamline access to quality care by improving payer-provider collaboration, cost containment, and healthcare economics. Cohere Health works with over 660,000 providers and handles over 12 million prior authorization requests annually. Its responsible AI auto-approves up to 90% of requests for millions of health plan members.
With the acquisition of ZignaAI, we’ve further enhanced our platform by launching our Payment Integrity Suite, anchored by Cohere Validate™, an AI-driven clinical and coding validation solution that operates in near real-time. By unifying pre-service authorization data with post-service claims validation, we’re creating a transparent healthcare ecosystem that reduces waste, improves payer-provider collaboration and patient outcomes, and ensures providers are paid promptly and accurately.
Cohere Health’s innovations continue to receive industry wide recognition. We’ve been named to the 2025 Inc. 5000 list and in the Gartner® Hype Cycle™ for U.S. Healthcare Payers (2022-2025), and ranked as a Top 5 LinkedIn™ Startup for 2023 & 2024. Backed by leading investors such as Deerfield Management, Define Ventures, Flare Capital Partners, Longitude Capital, and Polaris Partners, Cohere Health drives more transparent, streamlined healthcare processes, helping patients receive faster, more appropriate care and higher-quality outcomes.
The Coherenauts, as we call ourselves, who succeed here are empathetic teammates who are candid, kind, caring, and embody our core values and principles. We believe that diverse, inclusive teams make the most impactful work. Cohere is deeply invested in ensuring that we have a supportive, growth-oriented environment that works for everyone.
We can’t wait to learn more about you and meet you at Cohere Health!
Equal Opportunity Statement:
Cohere Health is an Equal Opportunity Employer. We are committed to fostering an environment of mutual respect where equal employment opportunities are available to all. To us, it’s personal.
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Senior Manager - Platform & Architecture
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About the role:
As a Sr. Manager, Platform & Architecture you will lead the definition, governance & continuous evolution of the enterprise data architecture vision and roadmap, ensuring strong alignment with business strategy and digital transformation goals. This role is accountable for establishing modern, secure, and scalable data platform architectures that enable advanced analytics, AI/ML, generative AI, and self service data capabilities across the organization.
You will provide strategic leadership in embedding AI into the enterprise data platform, enabling use cases such as predictive analytics, intelligent automation, and generative AI, while ensuring responsible AI practices, model governance, data quality, and regulatory compliance.
The role requires deep expertise in data architecture, cloud data platforms, analytics ecosystems, and platform security, combined with strong people and stakeholder management skills. You will guide the evaluation and adoption of emerging technologies, oversee PoC initiatives, and drive the operationalization of AI/ML and GenAI solutions.
Working closely with data engineering, analytics, AI/ML, security, and business leaders, you will ensure the delivery of trusted, high performing, and future ready data and AI platforms that scale with organizational needs.
What you'll do:
Strategic Leadership & Architecture Vision
- Define and own the enterprise data architecture vision and roadmap aligned with business strategy.
- Establish architectural principles, standards, and best practices across data modeling, integration, metadata, and analytics
- Guide architectural decisions to support scalability, performance, security, and future growth.
- Evaluate and approve new data technologies, platforms, and tools
Team Management & Development
- Lead, mentor, and manage data modelers & architects, platform engineers and data engineers
- Set goals, conduct performance reviews, and support career growth and skills development
- Ensure effective workload planning, prioritization, and resource allocation
- Promote a culture of collaboration, documentation, and architectural discipline
Data Platform & Architecture Design
- Design and oversee end to end data architectures, including ingestion, storage, processing, analytics, and consumption layers
- Define scalable patterns for batch, near real time, and streaming data processing
- Establish standards for data platforms, ingestion frameworks, transformation and modeling approaches, and BI/visualization tools
- Ensure platform reliability, performance, scalability, and cost optimization
Platform Engineering, Security & Governance
- Architect platforms with security by design, including IAM, RBAC, data encryption, masking, and auditing
- Collaborate with security and compliance teams to meet regulatory and data privacy requirements
- Define and enforce data governance standards, including metadata management, lineage, data quality, and observability
- Support platform monitoring, availability, and operational excellence
Advanced Analytics & Innovation
- Enable advanced analytics use cases, including forecasting, predictive modeling, and statistical analysis
- Support data science and analytics teams by designing architectures for ML pipelines, feature stores, and model deployment
- Lead Proof of Concept (PoC) initiatives to evaluate new data, analytics, and platform tools
- Assess emerging technologies for scalability, security, integration, and business value
Self-Service & Data Enablement
- Drive the self-service analytics strategy to empower analysts and business users
- Design curated, governed data layers and semantic models for trusted self-service access
- Reduce dependency on IT by enabling reusable data assets and standardized analytics frameworks
- Partner with stakeholders to align data products with business needs
Experience you'll need:
- Bachelor’s or Master’s degree in Computer Science, Engineering, Information Systems, or related field
- 10 - 15+ years of experience in data engineering, analytics, or platform architecture roles
- Strong experience designing and implementing modern data architectures and cloud data platforms.
- Hands-on and architectural experience with:
- Snowflake or similar cloud data warehouse/data lake experience
- Tableau or similar BI tools
- Fivetran or equivalent ingestion tools
- dbt or similar data transformation frameworks
- Proficiency in SQL, Python, Spark, and data modeling techniques.
- Experience with cloud platforms such as AWS, Azure, or GCP
Preferred Qualifications:
- Experience with advanced analytics, forecasting, and predictive modeling.
- Knowledge of ML/AI platforms and MLOps concepts.
- Strong understanding of data security, governance, and compliance frameworks.
- Excellent communication and stakeholder management skills.
- Experience working in large-scale or enterprise Data & Analytics environments.
Join Us in Securing and Accelerating the World's AI Transformation
Rubrik (RBRK), the Security and AI Operations Company, leads at the intersection of data protection, cyber resilience, and enterprise AI acceleration. Rubrik Security Cloud delivers complete cyber resilience by securing, monitoring, and recovering data, identities, and workloads across clouds. Rubrik Agent Cloud accelerates trusted AI agent deployments at scale by monitoring and auditing agentic actions, enforcing real-time guardrails, fine-tuning for accuracy and undoing agentic mistakes.
Linkedin | X (formerly Twitter) | Instagram | Rubrik.com
Inclusion @ Rubrik
At Rubrik, we are dedicated to fostering a culture where people from all backgrounds are valued, feel they belong, and believe they can succeed. Our commitment to inclusion is at the heart of our mission to secure the world’s data.
Our goal is to hire and promote the best talent, regardless of background. We continually review our hiring practices to ensure fairness and strive to create an environment where every employee has equal access to opportunities for growth and excellence. We believe in empowering everyone to bring their authentic selves to work and achieve their fullest potential.
Our inclusion strategy focuses on three core areas of our business and culture:
-
Our Company: We are committed to building a merit-based organization that offers equal access to growth and success for all employees globally. Your potential is limitless here.
-
Our Culture: We strive to create an inclusive atmosphere where individuals from all backgrounds feel a strong sense of belonging, can thrive, and do their best work. Your contributions help us innovate and break boundaries.
-
Our Communities: We are dedicated to expanding our engagement with the communities we operate in, creating opportunities for underrepresented talent and driving greater innovation for our clients. Your impact extends beyond Rubrik, contributing to safer and stronger communities.
Equal Opportunity Employer/Veterans/Disabled
Rubrik is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, or protected veteran status and will not be discriminated against on the basis of disability.
Rubrik provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability or genetics. In addition to federal law requirements, Rubrik complies with applicable state and local laws governing nondiscrimination in employment in every location in which the company has facilities. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.
Federal law requires employers to provide reasonable accommodation to qualified individuals with disabilities. Please contact us at hr@rubrik.com if you require a reasonable accommodation to apply for a job or to perform your job. Examples of reasonable accommodation include making a change to the application process or work procedures, providing documents in an alternate format, using a sign language interpreter, or using specialized equipment.
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About the Company
At Redpin, we simplify life’s most important payments. Buying a property overseas can be stressful—especially when it comes to moving money. Through our Currencies Direct and TorFX brands, we’ve been helping customers do exactly that for over 25 years.
With recent investment, we are building a new generation of digital products and services that make international real estate payments simpler, faster, and more transparent.
As part of Redpin 2.0, we are transforming from a horizontal FX platform into a verticalized, embedded software company, positioning ourselves as the global solution for real estate payments.
About the Role
At Redpin, this role is not just about managing infrastructure — it’s about building intelligent, scalable, and developer-first platforms that power our next-generation digital products.
As a Senior Software Engineer – DevOps, you will play a hands-on role in designing, building, and operating cloud-native infrastructure and DevOps platforms, with a strong emphasis on automation, reliability, security, and cost efficiency.
We are looking for a DevOps Engineer with exposure to AI/ML or Generative AI use cases, who can help us embed intelligence into our engineering ecosystem — from pipelines to observability and platform operations.
What You'll Do
AI / ML / GenAI
- Hands-on experience with platforms such as OpenAI, Bedrock, or Vertex AI
- Strong understanding of prompt engineering and AI API integrations
- Solid foundation in machine learning concepts and LLM architectures
Cloud Infrastructure (AWS)
- Design and implement AI-powered automation solutions for DevOps and platform engineering use cases
- Build and integrate AI agents to enhance developer productivity
- Develop and maintain CI/CD pipelines with AI-assisted workflows
- Design, provision, and operate secure, scalable AWS infrastructure
- Work across compute, networking, storage, and IAM
- Support multi-account AWS environments and apply governance guardrails
- Implement Infrastructure as Code (IaC) using Terraform and/or CloudFormation
- Troubleshoot and resolve cloud infrastructure issues
CI/CD & DevOps Automation
- Build, maintain, and optimize CI/CD pipelines for application and microservices teams (preferably using GitLab or GitHub)
- Automate build, test, security scanning, and deployments
- Implement deployment strategies such as blue-green, canary, and rolling deployments
- Improve pipeline performance, stability, and developer experience
Cloud Security & Governance (Execution Focus)
- Implement AWS security best practices including IAM, VPC security, encryption, and secrets management
- Enforce tagging standards, access controls, and policy guardrails
- Integrate security scanning (SAST, DAST, container scanning) into CI/CD pipelines
- Support audit and compliance requirements
Reliability & Observability
- Implement and manage monitoring, logging, and alerting solutions
- Build dashboards for system health, availability, and performance
- Improve system reliability through automation and proactive monitoring
Cloud Cost Optimization
- Monitor and optimize AWS costs across services.
- Implement right-sizing, autoscaling, and storage lifecycle policies.
- Support Savings Plans and Reserved Instance optimization.
- Promote cost-efficient cloud usage and architecture
DevOps Best Practices
- Apply and promote DevOps principles such as automation, CI/CD, and IaC.
- Reduce operational toil through tooling and automation.
- Support teams in adopting cloud-native and DevOps best practices
Collaboration & Mentorship
- Work closely with application, SRE, and security teams.
- Mentor junior DevOps engineers through code reviews and hands-on guidance.
- Contribute to documentation, runbooks, and operational standards
What You’ll Need
- Strong hands-on experience with AWS (EC2, EKS, ECS, VPC, IAM, RDS, S3, CloudWatch)
- Experience building AI agents or automation bots
- Familiarity with MLOps and FinOps practices
- Strong scripting skills (Python or Bash)
- Proven experience with CI/CD tools (GitLab CI, GitHub etc.)
- Strong experience with Infrastructure as Code (Terraform preferred)
- Hands-on experience with Docker and Kubernetes (EKS)
- Solid understanding of Linux, networking, and cloud security
- Experience with monitoring, logging, and alerting systems
- Strong troubleshooting and automation skills
Bonus Points
- AWS Config, CloudTrail, GuardDuty
- Observability tools (Corologix, ELK, Datadog)
- GitOps tools (ArgoCD, Flux)
- Scripting skills in Python, Go, or Bash
- Exposure to FinOps practices
- AWS Certified Solutions Architect – Associate or Professional
We welcome people from all backgrounds who seek the opportunity to help build a future where we connect the dots for international property payments. If you have the curiosity, passion, and collaborative spirit, work with us, and let’s move the world of PropTech forward together.
Redpin, Currencies Direct and TorFX are proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, colour, religion, national origin, disability, protected veteran status, age, or any other characteristic protected by law.
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Gen AI Lead
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Orion Innovation is a premier, award-winning, global business and technology services firm. Orion delivers game-changing business transformation and product development rooted in digital strategy, experience design, and engineering, with a unique combination of agility, scale, and maturity. We work with a wide range of clients across many industries including financial services, professional services, telecommunications and media, consumer products, automotive, industrial automation, professional sports and entertainment, life sciences, ecommerce, and education.
Role: GenAI Lead Engineer
Experience: 8+ years total (with significant hands-on GenAI / LLM work)
Job Overview:
We are seeking an innovative and highly skilled Lead Generative AI (GenAI) Engineer to spearhead the design, development, and deployment of advanced AI-powered solutions. In this role, you will lead a team of engineers and data scientists to harness cutting-edge Generative AI technologies and implement them to solve complex business problems, enhance user experiences, and drive innovation. This role combines deep technical expertise, leadership, and a strong understanding of AI trends and tools.
Key Responsibilities:
- Technical Leadership:
- Lead the end-to-end design and implementation of Generative AI solutions.
- Provide technical guidance and mentorship to engineers and data scientists working on GenAI projects.
- Stay updated with the latest trends, research, and advancements in Generative AI and Large Language Models (LLMs).
- Solution Development:
- Architect, train, and fine-tune state-of-the-art LLMs and generative AI models
- Develop and optimize pipelines for prompt engineering, retrieval-augmented generation (RAG), and domain-specific fine-tuning.
- Develop and deploy generative AI models, particularly focusing on ChatGPT, using Python on Azure or AWS Platform or .Net on Azure platform
- Ensure scalability, performance, and security of AI solutions deployed in production.
- Integration and Deployment:
- API Development: Ability to define and deliver API access for GenAI services, facilitating integration with other systems and applications.
- Collaborate with software engineering teams to integrate GenAI solutions into enterprise applications and services.
- Utilize cloud platforms (e.g., Azure, AWS, or GCP) to deploy and manage AI models and APIs.
- Leverage MLOps practices for continuous model monitoring, retraining, and improvement.
- Data Strategy and Preparation:
- Collaborate with data engineering teams to ensure high-quality data acquisition, preprocessing, and augmentation for model training and fine-tuning.
- Implement data governance and privacy practices in line with organizational policies.
- Innovation and Research:
- Experiment with new generative AI techniques, such as multimodal AI, reinforcement learning with human feedback (RLHF), and active learning.
- Evaluate and recommend AI frameworks, libraries, and platforms for project requirements.
- Stakeholder Collaboration:
- Work closely with product managers, business stakeholders, and UX designers to define AI-powered product features and use cases.
- Present technical concepts, project progress, and AI capabilities to non-technical audiences.
Key Requirements
- Technical Skills:
- Hands-on experience with cloud platforms and services for AI/ML, such as Azure AI Services, Azure Machine Learning, AWS Bedrock, or Google Vertex AI.
- Hands on experience in any of LLMs such as OpenAI’s ChatGPT Models , Gemini, Llama 2 ,Claude 2 ,Grok
- Hands on experience in any of the agentic frameworks like LangChain, Semantic kernel, AutoGen, CrewAi
- Hands on experience using any of vector database like Chroma, Pinecone, Weaviate, Faiss
- Experience with multimodal AI and advanced techniques like Tree-of-Thoughts, Retrieval-Augmented Generation (RAG), or Reinforcement Learning with Human Feedback (RLHF)
- Strong expertise in LLMs and generative AI frameworks like OpenAI, Hugging Face Transformers, or similar platforms.
- Deep understanding of natural language processing (NLP) concepts, including tokenization, embeddings, and sequence-to-sequence models.
- Proficiency in Python and libraries such as TensorFlow, PyTorch, and Scikit-learn.
- Experience in CI/CD pipeline management and automation tools, particularly within the Azure DevOps environment. Knowledge of containerization (e.g., Docker) and orchestration tools is also important
- Familiarity with MLOps tools and practices, such as MLflow, Kubeflow, or Docker.
Qualifications:
- Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field (Ph.D. preferred).
- 8+ years of experience in AI/ML engineering, with 2+ years specifically in Generative AI.
- Minimum of 2 years of experience in building Conversational AI applications using cloud-based services and in orchestrating AI/ML services for building a complete solution
- Minimum of 6 years of extensive full-time experience in Data Analysis, Statistics, Machine Learning, or Computer Science
- Proven track record of leading AI projects from inception to production.
- Experience with multimodal AI and advanced techniques like Tree-of-Thoughts, Retrieval-Augmented Generation (RAG), or Reinforcement Learning with Human Feedback (RLHF).
- Certifications in AI/ML or cloud platforms (e.g., Azure AI Engineer, AWS Certified Machine Learning).
Orion is an equal opportunity employer, and all qualified applicants will receive consideration for employment without regard to race, color, creed, religion, sex, sexual orientation, gender identity or expression, pregnancy, age, national origin, citizenship status, disability status, genetic information, protected veteran status, or any other characteristic protected by law.
Candidate Privacy Policy
Orion Systems Integrators, LLC and its subsidiaries and its affiliates (collectively, “Orion,” “we” or “us”) are committed to protecting your privacy. This Candidate Privacy Policy (orioninc.com) (“Notice”) explains:
- What information we collect during our application and recruitment process and why we collect it;
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Your use of Orion services is governed by any applicable terms in this notice and our general Privacy Policy.
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Solution Architect – (AI Infrastructure & Hybrid Cloud)
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About Gruve
Gruve is an innovative software services startup dedicated to transforming enterprises to AI powerhouses. We specialize in cybersecurity, customer experience, cloud infrastructure, and advanced technologies such as Large Language Models (LLMs). Our mission is to assist our customers in their business strategies utilizing their data to make more intelligent decisions. As a well-funded early-stage startup, Gruve offers a dynamic environment with strong customer and partner networks.
Position Summary:
We are seeking a Solution Architect – (AI Infrastructure & Hybrid Cloud) to lead the strategic design, architecture, and deployment of large-scale, enterprise-grade Red Hat OpenShift and Kubernetes environments. As a technical authority at the L4 level, you will be responsible for defining the blueprint of our cloud-native infrastructure, ensuring it is secure, scalable, and highly automated.
The ideal candidate acts as the bridge between traditional infrastructure and modern DevOps, serving as the lead design authority for global clients. You will collaborate with Network and Firewall Architects to build a unified fabric where containerized workloads, legacy data centers, and hybrid cloud environments coexist seamlessly through advanced automation and Infrastructure-as-Code (IaC).
Key Responsibilities:
- Architect and Design Enterprise OpenShift Solutions: Lead the high-level design (HLD) and low-level design (LLD) for multi-tenant Red Hat OpenShift and Kubernetes clusters across on-prem and hybrid cloud environments.
- Define the technology stack, standards, and blueprints for deploying AI solutions across global, multi-region public clouds (AWS/Azure/GCP) and diverse on-premise hardware.
- Oversee the successful end-to-end rollout of critical services including AI SOC, OpenShift AI, and AI-based Cybersecurity Log Optimization.
- Drive Network DevOps Strategy: Define and standardize the automation roadmap using Ansible, Terraform, and Python to achieve "Zero-Touch" infrastructure provisioning and configuration.
- Lead Customer & Stakeholder Engagement: Act as the primary technical consultant for global clients, leading design workshops, architecture validation, and executive-level technical reviews.
- Integrate Advanced AI apps, Networking & Security: Collaborate with Pre-sales, AI application developers & Engineers, Firewall Architects to design secure AI agents & use cases, container networking (CNI) models, implementing Zero-Trust security, service mesh (Istio), and micro-segmentation within OpenShift environment.
- Optimize Hybrid Infrastructure: Oversee the seamless integration of OpenShift with physical networking (Cisco ACI, VXLAN) and virtualized platforms (RHEL-V, VMware ESXi).
- GPU & Hardware Orchestration: Design and manage hardware acceleration using the NVIDIA GPU Operator and Node Feature Discovery (NFD). Implement Multi-Instance GPU (MIG) and time-slicing to optimize resource utilization across multi-tenant clusters.
- Establish CI/CD Governance: Architect robust CI/CD pipelines (Jenkins, GitLab CI, GitHub Actions) for infrastructure and application delivery, ensuring compliance and security are baked into the workflow.
- Lead Observability & Reliability: Design comprehensive monitoring and logging architectures using Prometheus, Grafana, and ELK stack to ensure 99.99% availability of cluster services.
- Mentorship & Technical Leadership: Guide and mentor L2/L3 engineers, providing expert-level escalation support and establishing best practices for the DevOps and Network teams.
- Innovation & R&D: Evaluate and introduce emerging technologies such as Advanced Cluster Management (ACM), Advanced Cluster Security (ACS), and Cloud-Native Networking (OVN-Kubernetes).
Basic Qualifications:
- Bachelor’s or master’s degree in computer science, Engineering, or a related field
- 10+ years of progressive experience in systems architecture, infrastructure engineering, or network DevOps.
- Expert/Architect-level proficiency in OpenShift (RHOS), and Kubernetes architecture in large-scale production environments.
- Experience architecting hybrid-cloud OpenShift solutions involving AWS (ROSA), Azure (ARO), or Google Cloud.
- Proven track record in Automation & IaC: Mastery of Ansible, Terraform, and Git-based workflows to manage complex infrastructures.
- Deep understanding of Linux (RHEL) Internals: Mastery of kernel networking, storage drivers (CSI), and container runtimes (CRI-O).
- Strong Network Background: In-depth knowledge of BGP, VXLAN, and EVPN as they apply to connecting containerized workloads to physical data center fabrics.
- Experience in "Architecture as Code": Ability to develop and maintain compliance artifacts, design validation reports, and automated documentation.
- Excellent Leadership Skills: Demonstrated ability to manage high-stakes customer relationships and lead cross-functional technical teams
Preferred Qualifications:
- Certifications: Red Hat Certified Architect (RHCA), Red Hat Certified Specialist in OpenShift (Administration/Development), or CKA/CKS (Certified Kubernetes Administrator/Security), AWS/GCP Certified DevOps Engineer, AWS Certified SysOps Administrator, HashiCorp Certified: Terraform Associate
- Red Hat Certified OpenShift Administrator, AWS Certified AI Practitioner, Certified Information Systems Security Professional (CISSP), Certified Cloud Security Professional (CCSP)
- Security Focus: Exposure to DevSecOps tools (e.g., Quay, StackRox) and zero-trust framework implementation
- Legacy Integration: Familiarity with Cisco ACI, Arista CloudVision, or Juniper Apstra for end-to-end automation integration
- Red Hat OpenShift AI (ROAI) expertise will be preferred
- Familiarity with LLM deployment requirements and vector database infrastructure
- Background in Cybersecurity infrastructure (SIEM, SOAR, SOC & VAPT platforms)
- Experience with MLOps infrastructure (Kubeflow, MLflow) and high-speed telemetry pipelines
Why Gruve
At Gruve, we foster a culture of innovation, collaboration, and continuous learning. We are committed to building a diverse and inclusive workplace where everyone can thrive and contribute their best work. If you’re passionate about technology and eager to make an impact, we’d love to hear from you.
Gruve is an equal opportunity employer. We welcome applicants from all backgrounds and thank all who apply; however, only those selected for an interview will be contacted.
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Senior Manager_MLE
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The Company
CommerceIQ is building the AI platform that runs commerce for the world's largest brands. We are not selling AI demos. We are shipping AI agents for content, media, and sales into the workflows of the Fortune 100 every week.
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2,200+
Customers
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10 of Top 12
CPG Companies
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900+
Retailers Connected
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$200M+
Raised
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Customers include Coca-Cola, Nestlé, Colgate-Palmolive, Mondelez, Samsung, and Kellogg's. Backed by SoftBank, Insight Partners, and Madrona. Headquartered in Mountain View with teams across the US, India, Canada, and the UK. Pre-IPO.
Company Overview
At CommerceIQ, we help consumer brands accelerate their retail ecommerce market share growth and profitability through machine learning algorithms. We are building the world’s most complete and sophisticated Retail Ecommerce Management Platform, which connects and intelligently automates the management of retail ecommerce channels like Amazon, Walmart, and Instacart, across the entire ecommerce operational chain of retail media management, sales operations, supply chain, and digital self analytics.
We are in hyper growth mode, having recently raised our Series D funding at unicorn valuation (>$1B) and ended our third year of triple-digit revenue growth. Continued acceleration of our growth is fueled by landing new customers, expanding our platform through new products, managing new retail ecommerce platforms, and delivering exceptional customer service to unlock high net retention rates.
What You’ll Be Doing
As a Lead ML Engineer in the Data Science team, you will work closely with the engineering, product, and operations teams to build state-of- the-art ML based solutions for B2B SaaS products. This will entail applying advanced ML algorithms at scale for core products and developing robust end to end production pipelines which includes Human-in-the-Loop component to boost the quality.
In this role, you will find innovative ways to apply emerging technologies to improve business processes and drive more value for customers. The ideal candidate will have a strong background in machine learning model development, natural language processing and understanding, and data analysis which they can utilize to manage and improve our company’s AI/ML initiatives.
- Architect and Own multiple AI driven end to end pipelines that allows for deployment and scalability of machine learning models
- Build tools and capabilities that help with data ingestion to feature engineering, data management and organization
- Build tools and capabilities for scalability through distributed optimization
- Deploy cutting edge algorithms like LLMs etc. on GPUs at scale
- Work with stakeholders on the research and software engineering side of the company to understand how to support their teams
- Build tools and capabilities for model management and model performance monitoring
- Build operating services at scale with high availability and reliability
- Propose and implement the best engineering practices for scaling ML-powered features, with a goal to enable the fast iteration of and efficient experimentation with novel features
- Contribute and influence the ML infrastructure roadmap in collaboration with Data Science team
What we are looking for -
- Bachelor’s or Masters in Computer Science or Maths/Stats from a reputed college with 5+ years of experience in solving of experience in machine learning engineering problems
- Experience and understanding of the entire machine learning pipeline from data ingestion to production
- Experience with machine learning operations, software engineering, and architecture
- Experience with large-scale systems including parallel computing and GPUs
- Experience architecting and building an AI pipelines that supports productionization of ML models
- Experience with MLOps systems
- Strong programming skills in a scientific computing language such as Python, SQL
- Experience using frameworks for machine learning and data science like scikit-learn, pandas, NumPy
- Experience working with ML tools such as Tensorflow, Keras, and Pytorch
- Ability to take successful, complex research ideas from experimentation to production
- Excellent written and oral communication skills and the capability to drive cross-functional requirements with product and engineering teams
- Good depth and breadth in machine learning (theory and practice), optimization methods, data mining, statistics and linear algebra
Why you will love to work with us -
We have multiple brands, which are among the biggest brands operating on amazon, as our customers. You will be responsible for working with their data and developing models and algorithms to drive lift in tune of hundreds of thousands of dollars.
- Opportunity to work on cutting edge technologies in text and images data like LLMs, OCR, transformer based embeddings models
- Deploy code using the most sophisticated tech stack like AWS, GCP etc.
- You will own projects end to end i.e., from exploration to final production
- You will be empowered to make decisions. It implies more responsibilities but high learning
- Immense opportunities to learn and develop ML based SaaS products for brands and get company-wide recognition
- Forget endless meetings. Get things done and start making an impact from day 1
- Work hard, have amazing fun, create history, build the future of eCommerce
- Start-up environment with a strong culture and values to accelerate your career
We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, disability status or any other category prohibited by applicable law.
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Apply to CommerceIQAt Anaplan, we are a team of innovators focused on optimizing business decision-making through our leading AI-infused scenario planning and analysis platform so our customers can outpace their competition and the market.
What unites Anaplanners across teams and geographies is our collective commitment to our customers’ success and to our Winning Culture.
Our customers rank among the who’s who in the Fortune 50. Coca-Cola, LinkedIn, Adobe, LVMH and Bayer are just a few of the 2,400+ global companies who rely on our best-in-class platform.
Our Winning Culture is the engine that drives our teams of innovators. We champion diversity of thought and ideas, we behave like leaders regardless of title, we are committed to achieving ambitious goals, and we love celebrating our wins – big and small.
Supported by operating principles of being strategy-led, values-based and disciplined in execution, you’ll be inspired, connected, developed and rewarded here. Everything that makes you unique is welcome; join us and let’s build what’s next - together!
About the Role
Anaplan is on a mission to revolutionize business planning by connecting organizations and people to make better, faster decisions. We are seeking a visionary Senior Manager for AI Engineering to lead our talented team in building the next generation of intelligent planning solutions. This is a critical leadership role where you will drive the technical strategy and execution for AI/ML initiatives, directly impacting Anaplan’s product and our customers' success. You will be at the forefront of integrating cutting-edge AI, from time series forecasting to generative and agentic AI, into our market-leading platform.
Key Responsibilities
- Lead, mentor, and grow a high-performing team of AI/ML engineers, fostering a culture of innovation, collaboration, and excellence.
- Define and execute the roadmap for AI/ML projects, ensuring alignment with business objectives and product strategy.
- Architect and oversee the development of scalable, robust, and production-grade AI systems on cloud platforms (AWS, Azure, GCP).
- Drive best practices for the full machine learning lifecycle, including MLOps, CI/CD for ML, model monitoring, and governance.
- Collaborate closely with product managers, data scientists, and other engineering leaders to translate business requirements into technical solutions.
- Stay at the forefront of advancements in AI/ML, including Large Language Models (LLMs) and agentic AI, to identify and implement new opportunities.
- Manage project timelines, resources, and stakeholder communication to ensure the timely delivery of high-quality AI solutions.
Required Qualifications
- Proven experience leading AI/ML teams in a SaaS or enterprise software environment.
- Deep expertise in time series forecasting and machine learning.
- Experience architecting and deploying scalable, production-grade AI systems on cloud platforms (AWS, Azure, GCP).
- Solid understanding of MLOps, CI/CD for ML, and cloud-native architectures.
- Deep knowledge of LLM APIs, prompt engineering, and conversational AI patterns.
- Experience with agentic frameworks and autonomous agent architectures.
- Proficiency in Python and modern software development practices (testing, code review, CI/CD).
- Proven track record of delivering complex technical projects on time with high quality.
- Excellent communication, collaboration, and stakeholder management skills.
- Track record of delivering impactful AI solutions in a fast-paced, agile environment.
Preferred Qualifications
- Master’s or Ph.D. in Computer Science, AI, Machine Learning, or a related field.
- Experience with large-scale data processing frameworks like Spark.
- Familiarity with the challenges of applying AI in enterprise planning or financial domains.
- A portfolio of published research or contributions to open-source AI projects.
- 10 Years +
What Makes This Role Exciting
You will be a key leader in Anaplan’s AI journey, with the autonomy to shape our technical direction and build a world-class engineering team. This is a unique opportunity to solve complex, real-world problems and deliver intelligent solutions that empower major global enterprises to make more informed decisions. You will work with a passionate team on the cutting edge of AI, making a tangible impact on our product and the industry.
Our Commitment to Diversity, Equity, Inclusion and Belonging (DEIB)
We believe attracting and retaining the best talent and fostering an inclusive culture strengthens our business. DEIB improves our workforce, enhances trust with our partners and customers, and drives business success. Build your career in a place where diversity, equity, inclusion and belonging aren’t just words on paper – this is what drives our innovation, it’s how we connect, and it contributes to what makes us a market leader. We believe in a hiring and working environment where all people are respected and valued, regardless of gender identity or expression, sexual orientation, religion, ethnicity, age, neurodiversity, disability status, citizenship, or any other aspect which makes people unique. We hire you for who you are, and we want you to bring your authentic self to work every day!
We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, perform essential job functions, and receive equitable benefits and all privileges of employment. Please contact us to request accommodation.
Fraud Recruitment Disclaimer
It has come to our attention that fraudulent and fictitious job opportunities are being circulated on the Internet. Prospective candidates are being contacted by certain individuals, mainly through telephone calls, emails and correspondence, claiming they are representatives of Anaplan. The main purpose of these correspondences and announcements is to obtain privileged information from individuals.
Anaplan does not:
- Extend offers to candidates without an extensive interview process with a member of our recruitment team and a hiring manager via video or in person.
- Send job offers via email. All offers are first extended verbally by a member of our internal recruitment team whenever possible and then followed up via written communication.
All emails from Anaplan would come from an @anaplan.com email address. Should you have any doubts about the authenticity of an email, letter or telephone communication purportedly from, for, or on behalf of Anaplan, please send an email to people@anaplan.com before taking any further action in relation to the correspondence.
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Lead Developer [Full stack + AI]
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Lead Developers act as the primary point of contact for our clients, ensuring that teams are successful in their delivery. In this role, you will bring a strategic mindset to projects and spend time collaborating and negotiating with clients to bring a technical vision to life. Having a balance of high-level and tactical mindsets is a must, as you will spend time both with clients and your teammates.
At Thoughtworks, we believe in going above and beyond the standard and are committed to delivering best-in-class solutions that exceed our clients' expectations. Our standard engineering and delivery practices reflect our commitment to quality, and our team is always looking to innovate and improve. Lead Developers guide and coach their teams in their implementation and application.
Job responsibilities
- You will champion and adopt best practices like writing clean and reusable code using TDD, pair programming and design patterns
- You will oversee or take part in the entire cycle of software consulting and delivery from ideation to evolution in production and everything in between
- You will use and advocate for continuous delivery practices to deliver high-quality software as well as value to end customers as early as possible
- You will design solutions and choose technologies that solve clients’ problems while working within constraints and make pragmatic tradeoffs
- You will collaborate with a variety of teammates to build features, design concepts and interactive prototypes and ensure best practices and UX specifications are embedded along the wayYou will apply the latest technology thinking from our Technology Radar to solve client problems
- You will apply a variety of languages and tools to your work and continue to code alongside Developers; you will not be post-technical in this role
- You will efficiently utilize and champion DevSecOps tools and practices to build and deploy software, advocating devops culture and shifting security left in development
- You will cultivate Thoughtworker growth and development by encouraging feedback and fostering an inclusive, supportive team culture
Job qualifications
Technical Skills
- Should have 8+years of experience in designing and developing scalable, secure, and maintainable applications using Java, JavaScript, Python, or equivalent technologies.
- Design end‑to‑end Salesforce technical architecture across Sales Cloud.
- Define system integration patterns between Salesforce and external systems (REST/SOAP, middleware, ETL, APIs)
- Define and review Architecture Decision Records (ADR), ensuring alignment with performance, security, and business goals.
- Enforce engineering excellence through sensible defaults, clean coding standards, and proactive tech debt management.
- Review and optimize BigQuery SQL or equivalent data scripts for performance and scalability.
- Understanding of data processing, model inference, and MLOps best practices.
- Drive end-to-end delivery, ensuring alignment with SDLC processes, coding standards, and quality benchmarks.
- Manage sprint-level planning, estimation, and delivery tracking, proactively identifying risks and mitigation plans.
- Own technical reviews, release readiness, and deployment oversight for assigned projects.
- Lead teams following Agile and XP practices — pair programming, TDD, CI/CD, and continuous feedback.
- Collaborate across cross-functional teams (QA, DevOps, Product) to ensure smooth delivery.
- Foster a team-first culture, ensuring collaboration, transparency, and continuous improvement.
- Design and manage cloud-native deployments on AWS, GCP, or Azure.
- Ensure effective use of CI/CD tools (CircleCI, GitHub Actions, Jenkins, etc.) for automated, secure pipelines.
- Hands-on with Google Cloud Platform (GCP) — Pub/Sub, BigQuery, Cloud Functions, Cloud Run, Kubernetes, IAM.
- Experience with AI-First Software Delivery (AIFSD) — using LLMs, generative AI APIs, or AI-assisted coding.
- Exposure to microservices architecture, event-driven systems, or message queues (Kafka, Pub/Sub, RabbitMQ).
Professional Skills
- You have experience influencing others and always advocate for technical excellence while being open to change when needed
- You bridge product and technology by helping to translate business needs to software requirements
- You have the ability to develop and execute a technical vision with a focus on business value
- You will act as a mentor for less experienced peers through both your technical knowledge and ability to inspire a team to deliver extraordinary impact together
- You’re resilient in ambiguous situations and can approach challenges from multiple perspectives
Other things to know
Learning & Development
There is no one-size-fits-all career path at Thoughtworks: however you want to develop your career is entirely up to you. But we also balance autonomy with the strength of our cultivation culture. This means your career is supported by interactive tools, numerous development programs and teammates who want to help you grow. We see value in helping each other be our best and that extends to empowering our employees in their career journeys.
Onsite Work Expectation
You may be expected to work out of our Thoughtworks office or at our client's office location for all five working days of the week, depending on business or clients’ needs.
About Thoughtworks
Thoughtworks is a global technology consultancy that integrates strategy, design and engineering to drive digital innovation. For 30+ years, our clients have trusted our autonomous teams to build solutions that look past the obvious. Here, computer science grads come together with seasoned technologists, self-taught developers, midlife career changers and more to learn from and challenge each other. Career journeys flourish with the strength of our cultivation culture, which has won numerous awards around the world.
Join Thoughtworks and thrive. Together, our extra curiosity, innovation, passion and dedication overcomes ordinary.
Ready to apply?
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Director-Strategic Technical Advisory
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What Cognite is: Relentless to achieve
Cognite operates at the forefront of industrial digitalization, building AI, and data solutions that solve the world’s hardest, highest-impact problems. With unmatched industrial heritage and a comprehensive suite of AI capabilities, including low-code AI agents, Cognite accelerates the digital transformation to drive operational improvements.
We thrive in challenges. We challenge assumptions. We execute with speed and ownership. If you view obstacles as signals to step forward - not backwards - you’ll feel right at home here.
Our Moonshot is bold: Unlock $100B in customer value by 2035, and redefine how global industry works. Join us in this venture where AI and data meet ingenuity, and together, we will forge the path to a smarter, more connected industrial future.
Our values
Impact: Cogniters strive to make an impact in all that they do. We are result-oriented, always asking ourselves.
Ownership: Cogniters embrace a culture of ownership. We go beyond our comfort zones to contribute to the greater good, fostering inclusivity and sharing responsibilities for challenges and success.
Relentless: Cogniters are relentless in their pursuit of innovation. We are determined and deliverable (never ruthless or reckless), facing challenges head-on and viewing setbacks as opportunities for growth.
Introduction
We are seeking a dynamic and experienced Strategic Technical Advisor to spearhead the growth and operational excellence of our dedicated technical delivery and enablement function focused exclusively on our strategic customer. Crucially, this Hub operates as a key component of the larger Strategic Program organization dedicated to this customer.
This is a foundational role in a high-potential environment, as the Hub team will grow from an initial 6 technical resources to approximately 20 by the end of the year.
The successful candidate will be responsible for three critical outcomes:
- Hub Build-Out: Hiring the team, establishing the operational frameworks, best practices, and culture necessary to scale successfully and ensuring seamless integration with the strategic customer's priorities and the Strategic Program's goals.
- Delivery Excellence: Guaranteeing the high-quality, successful, and impactful delivery of technical solutions, customer support and enablement programs for the customer.
- Ecosystem Enablement: Developing and mentoring a 3rd party partner team to ensure they can independently support and extend the customer's platform usage.
The role requires a strong dual focus: Team Leadership and Technical Oversight. As the entire team consists of specialized technical resources—specifically Data Scientists, Data Engineers, and Solution Architects—and includes an integrated, dedicated Support function, the Hub Lead must act as a mentor and technical guide. They will be expected to direct and coach these technical experts on how to "show up" with professionalism and technical authority in complex, high-stakes customer-facing engagements.
Key Responsibilities
1. Technical Mentorship & Partner Enablement
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Team Mentorship |
Act as the primary mentor to the dedicated Data Engineers, Data Scientists, and Solution Architects. Provide deep-level guidance on system design, challenging technical assumptions to ensure scalable, robust solutions that align with the strategic customer's industrial context |
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Partner Enablement Strategy |
Lead the technical strategy for the partner enablement program. Directly audit and coach internal mentors to ensure 3rd party partner staff meet rigorous engineering standards and architectural best practices for customer delivery. |
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Customer-Facing Excellence |
Define and enforce rigorous standards for professional conduct and presence specific to the strategic customer's culture, ensuring the team communicates technical concepts clearly and represents the firm with integrity and expertise. |
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Solution Delivery Guidance |
Direct the team on the appropriate technical approach and methodology for project execution (e.g., solution design documentation, code quality, data modeling standards) specific to the customer's environment. |
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Effective Stakeholder Coaching |
Coach team members on translating technical findings into business-relevant language for non-technical stakeholders in the program and customer. |
2. Program Collaboration & Cross-Functional Coordination
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Strategic Program Alignment |
Collaborate closely with the leadership and functional teams of the larger Strategic Program to ensure the Hub's delivery priorities, technical roadmaps, and resource assignments are fully aligned with the overall Program's goals and milestones. |
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Dedicated Support Direction |
Serve as the technical lead for the Dedicated Customer Support team. Prioritize day-to-day technical tasks and troubleshoot complex system issues, ensuring technical SLAs are met within the Strategic Program structure. |
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Academy & Community Collaboration |
Liaise directly with the Academy and Community teams to ensure the strategic customer and its partners effectively leverage standard coursework. Actively contribute to the knowledge exchange, ensuring the team is at the forefront of platform capabilities. |
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Custom Content Development |
Partner with the Academy team as required to develop specialized or custom coursework, training materials, and certification pathways tailored to the strategic customer's unique platform configuration or industrial challenges. |
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Risk & Dependency Management |
Proactively manage technical risks and cross-project dependencies that impact the customer, ensuring effective communication of mitigation strategies to the Strategic Program and customer stakeholders. |
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Deep - Dive Retrospectives |
Lead thorough technical retrospectives. Focus on code quality, performance bottlenecks, and architectural improvements to drive continuous technical excellence. |
3. Delivery Excellence & Customer Success
- Standards Implementation: Establish and enforce adherence to defined technical delivery standards and best practices on all projects, specifically tailored to meet the customer’s technical environment and compliance requirements.
- Escalation Management: Execute the internal escalation process for critical customer issues, ensuring timely resolution and coordinated communication with customer and support teams.
- Customer Feedback and Improvement: Analyze customer feedback and system performance data to propose and implement actionable improvements to engineering methodologies, developer tools, or team workflows.
4. Financial and Operational Performance
- Estimations & Scope Creep: Work with Program Managers to maintain accurate technical effort forecasts. Proactively flagging technical scope creep or resource bottlenecks.
5. Talent Acquisition and Development
- Recruitment and Onboarding: Lead the deep-dive technical interview and selection process for all Hub candidates. Ensure every new hire raises the collective technical bar of the team.. Own and manage the complete onboarding process for new team hires.
- Engagement & Retention: Drive employee engagement for this dedicated team through regular check-ins and activities, using proactive measures to address retention risks.
- Training Strategy Execution: Develop and execute comprehensive training and upskilling plans that focus on both deep technical skills and customer-specific domain knowledge, leveraging standard Academy content while ensuring the Dedicated Support team is current on the customer's architecture and configuration.
- Knowledge Sharing Facilitation: Actively facilitate collaborative team work sessions to encourage knowledge sharing and capture team-developed process improvements or technical solutions to share with the broader organization.
- External Partner Quality: Track and report on the effectiveness and quality of the 3rd party partner staff to ensure skill and knowledge levels meet delivery and performance standards.
Key Performance Indicators (KPIs)
The Strategic Customer Hub Lead is accountable for monitoring and reporting on the following key metrics:
- Partner Readiness: Achieve [Metric/Level] in partner certification and readiness tracking.
- Customer Enablement : Track customer and partner completion rates for Academy coursework and Community engagement levels.
- Talent Retention & Engagement: Achieve and maintain a voluntary attrition rate below [Z]%.
Qualifications
- Technical Domain Expertise: Minimum of 15+ years of professional experience in a technical discipline relevant to the team (e.g., Data Engineering, Cloud Architecture, or Data Science/MLOps) ideally in a SaaS environment. Must have at least 5 years of experience in a role that required reviewing architecture and challenging technical decisions made by senior engineering staff.
- Strategic Account Experience: Proven history of successfully leading technical delivery for a singular, large strategic customer or within a dedicated account structure. Demonstrated ability to navigate complex enterprise IT landscapes and align internal technical roadmaps with client-side architectural constraints.
- Architectural Governance & Program Alignment: Ability to operate effectively within a matrixed Strategic Program, serving as the "technical conscience" of the Hub to ensure all deliveries align with the broader program's long-term technical objectives. Experience providing technical direction to dotted-line support resources is essential.
- Partner & Learning Enablement: Demonstrated ability to mentor, train, or enable a 3rd party partner and to effectively leverage or develop formal learning pathways (Academy/training) for customer success.
- Team Building & Mentorship: Extensive experience in mentoring and coaching highly skilled technical professionals, specifically within an Indian delivery center context.
- Communication & Presence: Exceptional verbal and written communication skills necessary to articulate technical strategy to executive-level clients and effectively train team members on professional presence (the "how to show up" factor).
Join the global Cognite community! 🌐
- Join an organization of 70 different nationalities 🌐 with Diversity, Equality and Inclusion (DEI) in focus 🤝
- ITPL office location (Bengaluru)
- A highly modern and fun working environment with sublime culture across the organization, follow us on Instagram @cognitedata 📷 to know more
- Flat structure with direct access to decision-makers, with minimal amount of bureaucracy
- Opportunity to work with and learn from some of the best people on some of the most ambitious projects found anywhere, across industries
- Join our HUB 🗣️ to be part of the conversation directly with Cogniters and our partners.
- Hybrid work environment globally
Why choose Cognite? 🏆 🚀
Join us in making a real and lasting impact in one of the most exciting and fastest-growing new software companies in the world. We have repeatedly demonstrated that digital transformation, when anchored on strong DataOps, drives business value and sustainability for clients and allows front-line workers, as well as domain experts, to make better decisions every single day. We were recognized as one of CNBC's top global enterprise technology startups powering digital transformation! And just recently, Frost & Sullivan named Cognite a Technology Innovation Leader! 🥇
- Impact 2025
- Cognite's Industrial AI: Moonshot
- We’re globally recognized domain experts with an international presence that spans Phoenix, Houston, Oslo Tokyo, Bengaluru, and Abu Dhabi.
Ready to apply?
Apply to Cognite - AI for Industry
Lead AI Engineer & Technical Architect (Remote)
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About Bold Business
Bold Business is an AI-first U.S. based global workforce solutions company rebuilding how businesses operate in the AI era. We build AI-Amplified Talent™, custom AI agents, and automation systems for clients like AT&T, JP Morgan, and Verizon — and we back every engagement. If you want to build things that ship and matter, you'll fit right in.
The Role
You are the technical standard-setter and primary builder for how AI systems are designed, built, and shipped at Bold.
You will:
- Architect systems
- Build them yourself
- Set the bar for everyone else
If you haven’t personally shipped production AI systems end-to-end, this role will not be a fit.
What You’ll Do
Build Real Systems
- Design and ship production RAG pipelines (end-to-end)
- Build multi-agent systems used by real clients
- Integrate LLMs into production workflows (not prototypes)
- Own backend systems (FastAPI, multi-tenant, secure)
- Deploy with Docker + CI/CD + cloud
- Measure and improve output quality before anything ships
Set the Standard
- Define how AI systems are built at Bold
- Establish architecture patterns, prompting standards, and data flows
- Own code quality and reviews — nothing ships without your approval
- Choose tools, frameworks, and infrastructure
- Mentor engineers and raise the performance bar across the team
Non-Negotiable Requirements
English communication — non-negotiable
- Advanced to fluent English — written and spoken
- Ability to explain technical concepts clearly to non-technical stakeholders: clients, founders, business owners
- Professional written communication across emails, Slack, documentation, and status updates
- Comfortable on video calls and async communication with a U.S.-based team
RAG (This Defines the Role)
- You have shipped 2+ production RAG systems (not demos)
- You can explain every decision (chunking, embeddings, retrieval, re-ranking)
- You’ve worked with vector databases in production
- You’ve debugged real issues (hallucination, low recall, bad retrieval)
- You’ve built multi-tenant systems with clean data separation
- You know how to measure and improve output quality
Core Engineering
- 5+ years Python in production
- 3+ years building AI/LLM systems used by real users
- LangChain / LangGraph in production (not tutorials)
- Experience designing multi-agent systems
- Strong backend experience (FastAPI or equivalent)
- Docker, CI/CD, cloud deployment
- Security fundamentals (auth, secrets, isolation)
- Strong written English (clear, direct, professional)
- Proven ability to set and enforce engineering standards
Strong Signals (Highly Valued)
- LlamaIndex, hybrid search, or re-ranking models
- RAG over complex data (PDFs, tables, images)
- Open-source LLMs (Ollama, vLLM)
- MLOps, evaluation, monitoring
- Voice AI pipelines
- Experience leading technical direction for a team
- Client-facing delivery experience
Who You Are
- You build and think in systems, not just features
- You don’t wait to be unblocked — you solve it
- You care about clean, scalable systems in production
- You can explain complex systems simply
- You push standards higher, even when it’s uncomfortable
Experience: 5–8 years
Proof: Live systems with real users (required)
How We Evaluate You
We will ask you to:
- Walk through a system you built in detail
- Explain your architectural decisions
- Build a working RAG pipeline
- Show how you think, not just what you know
Bold Business
AI-First. Standards-First. Delivery-First.
We build systems that ship, scale, and earn trust.
About Bold Business:
Bold Business is a US-based global business process outsourcing (BPO) firm with over 25 years of experience and $7B+ in client engagements. We help fast-growing companies scale through smart talent strategies, automation, and technology-driven solutions.
Bold Business recruiters always use a “@boldbusiness.com” email address and/or from our Applicant Tracking System, Greenhouse. Any variation of this email domain should be considered suspicious. Additionally, Bold Business recruiters and authorized representatives will never request sensitive information in email or via text.
Ready to apply?
Apply to Bold Business
About Payoneer
Founded in 2005, Payoneer is the global financial platform that removes friction from doing business across borders, with a mission to connect the world’s underserved businesses to a rising global economy. We’re a community with over 2,500 colleagues all over the world, working to serve customers, and partners in over 190 countries and territories.
By taking the complexity out of the financial workflows–including everything from global payments and compliance to multi-currency and workforce management, to providing working capital and business intelligence–we give businesses the tools they need to work efficiently worldwide and grow with confidence.
Role Summary
We are seeking a Lead Engineer, AI Systems to serve as the technical anchor across our AI-augmented engineering organisation. This role bridges our Senior AI Coding Engineers, the AI/ML Developer (SLM Specialist), and the Agentic Systems intern cohort. You will set technical direction, own cross-cutting architectural decisions, and champion the responsible, high-impact adoption of AI-assisted development practices across the entire engineering function.
You will remain hands-on with code while simultaneously shaping how the wider team builds, evaluates, and ships AI-powered products.
Key Responsibilities
1 Technical Vision & Architecture
- Define and own the end-to-end technical architecture for AI Systems — spanning product feature surfaces, model inference APIs, and agentic toolchains.
- Drive Architecture Decision Records (ADRs), system design reviews, and RFC processes across squads.
- Establish standards for integrating SLM/LLM model endpoints into product surfaces built by the Senior Engineering team.
- Evaluate emerging AI infrastructure patterns (RAG, agentic orchestration, vector stores, model serving) and guide adoption decisions.
- Own the technical roadmap for AI tooling, developer productivity, and model integration layers.
2 Cross-Squad Technical Leadership
- Act as the primary technical liaison between the AI/ML Developer (model side) and Senior Engineers (product side), ensuring smooth API contracts, evaluation loops, and deployment handoffs.
- Provide technical direction to Agentic Systems interns, reviewing designs, code, and agentic pipeline implementations.
- Unblock senior engineers on hard architectural or integration challenges that span squad boundaries.
- Run cross-team design reviews, architecture syncs, and engineering guild sessions.
3 AI-Augmented Engineering Excellence
- Define and maintain the organisation’s standards for AI-assisted development — covering context engineering, AI code review protocols, context management, and tool evaluation criteria.
- Maintain and evolve the internal AI tooling playbook (Cursor IDE, Claude Code, Codex CLI, and emerging tools).
- Evaluate new AI coding tools, agentic frameworks (LangChain, LlamaIndex, CrewAI, AutoGen), and developer-productivity platforms; produce adoption recommendations with measured trade-offs.
- Conduct structured audits of AI-generated code across squads for correctness, security, and maintainability.
4 Hands-On Engineering
- Remain an active contributor: own critical-path features, prototype architectural spikes, and build shared infrastructure components used across squads.
- Personally drive resolution of the most complex production incidents and root-cause analyses.
- Review and merge high-impact PRs; maintain the highest code review quality bar on the team.
- Own observability and reliability for AI inference and MLOps integration layers in production.
5 Mentoring & Talent Development
- Mentor Senior Engineers, the AI/ML Developer, and interns through technical coaching, design feedback, and stretch assignments.
- Lead hiring panels and technical interviews; help define and uphold the engineering hiring bar.
- Contribute to onboarding frameworks that embed AI-first practices from day one.
- Model a culture of rigorous experimentation, psychological safety, and continuous improvement.
6 Stakeholder & Product Collaboration
- Partner with the Director of Engineering and Product leadership to translate product strategy into a phased technical roadmap.
- Present architectural proposals and trade-off analyses to engineering leadership and executive stakeholders as required.
- Coordinate with DevOps/Platform teams on GPU/TPU compute provisioning, CI/CD for model pipelines, and cloud cost optimisation.
Required Qualifications
1 Education
- Bachelor’s or Master’s degree in Computer Science, or a related field.
- Candidates without a degree but with a compelling portfolio demonstrating scope and impact at staff/lead level will be considered.
2 Experience
- 6 – 8 years of professional software engineering experience in product-focused environments.
- Minimum 2 years in a formal or de-facto technical lead / staff engineer capacity across multiple squads or systems.
- Minimum 8-12 months of active, hands-on experience with AI coding tools in a professional engineering setting.
- Proven track record of shipping production systems with measurable business impact at scale.
- Demonstrated experience collaborating closely with ML/AI model teams on integration, deployment, and evaluation.
3 Technical Skills — Core Engineering
- Languages: Expert proficiency in at least two of — Python, TypeScript/JavaScript, Go.
- Architecture: Microservices, event-driven systems, API design (REST, GraphQL, gRPC), distributed systems fundamentals.
- Databases: SQL (PostgreSQL, MySQL) and NoSQL (MongoDB, Redis); vector databases (FAISS, Pinecone, Weaviate).
- Cloud: AWS, GCP, or Azure — compute, storage, serverless, managed ML services (SageMaker, Vertex AI).
- DevOps: Docker, Kubernetes, CI/CD (GitHub Actions, Jenkins); IaC (Terraform/Pulumi); observability stacks.
- Testing: TDD/BDD; unit, integration, and e2e frameworks; model evaluation pipelines.
4 AI / ML Integration Skills (Mandatory)
- Demonstrated proficiency with AI coding assistants (Cursor IDE, Claude Code, Codex CLI) in daily professional workflows.
- Experience designing and consuming LLM/SLM inference APIs; understanding of model serving, latency, and cost trade-offs.
- Hands-on familiarity with RAG architectures, vector stores, and retrieval pipelines.
- Ability to define and enforce AI code quality standards across an engineering team.
- Understanding of LLM limitations: hallucinations, context window constraints, prompt injection risks, and licensing considerations.
5 Technical Skills — Nice to Have
- Experience with SLM/LLM training or fine-tuning pipelines (SFT, RLHF, LoRA/QLoRA).
- Familiarity with agentic frameworks (LangChain, LlamaIndex, AutoGen, CrewAI) and multi-step reasoning pipelines.
- Contributions to open-source ML or developer tooling projects.
- Knowledge of OWASP Top 10, secure coding, and AI-specific security risks (prompt injection, model exfiltration).
- Prior experience in a high-growth startup or scale-up environment with rapid iteration cycles.
Behavioural Competencies
- AI-First Mindset: Defaults to AI tools to accelerate work while maintaining rigorous quality standards; actively pushes the team’s AI capability forward.
- Systems Thinking: Sees the full picture — how model outputs, product surfaces, and infrastructure interdepend; anticipates second-order effects of architectural choices.
- Ownership: Takes end-to-end responsibility from design through production; doesn’t hand off problems, solves them.
- Influence Without Authority: Earns trust through technical credibility; drives alignment through persuasion, data, and well-reasoned proposals.
- Communication: Writes clear design docs, ADRs, and post-mortems; articulates complex trade-offs for engineering peers and non-technical stakeholders.
- Mentorship: Actively invests in the growth of engineers at all levels; gives direct, constructive feedback.
- Pragmatism: Balances the ideal with the shipped; knows when to iterate vs. refactor vs. rewrite.
- Curiosity: Continuously explores emerging research, tools, and patterns — and brings those learnings back to the team.
The Payoneer Ways of Working
Act as our customer’s partner on the inside
Learning what they need and creating what will help them go further.
Do it. Own it.
Being fearlessly accountable in everything we do.
Continuously improve
Always striving for a higher standard than our last.
Build each other up
Helping each other grow, as professionals and people.
If this sounds like a business, a community, and a mission you want to be part of, apply today.
We are committed to providing a diverse and inclusive workplace. Payoneer is an equal opportunity employer, and all qualified applicants will receive consideration for employment no matter your race, color, ancestry, religion, sex, sexual orientation, gender identity, national origin, age, disability status, protected veteran status, or any other characteristic protected by law. If you require reasonable accommodation at any stage of the hiring process, please speak to the recruiter managing the role for any adjustments. Decisions about requests for reasonable accommodation are made on a case-by-case basis.
Ready to apply?
Apply to Payoneer
About Payoneer
Founded in 2005, Payoneer is the global financial platform that removes friction from doing business across borders, with a mission to connect the world’s underserved businesses to a rising global economy. We’re a community with over 2,500 colleagues all over the world, working to serve customers, and partners in over 190 countries and territories.
By taking the complexity out of the financial workflows–including everything from global payments and compliance to multi-currency and workforce management, to providing working capital and business intelligence–we give businesses the tools they need to work efficiently worldwide and grow with confidence.
Role Summary
We are looking for a technically strong AI / ML Developer with hands-on expertise in training and fine-tuning Small Language Models (SLMs) and RAG Solutions. The ideal candidate will drive end-to-end AI Solutions — from dataset curation and pre-processing to training, evaluation, and production deployment. You will collaborate closely with product, product engineers, and infrastructure teams to build AI solutions that are efficient, scalable, and business-aligned.
Key Responsibilities
1 Model Design & Training
- Design, train, and fine-tune Small Language Models (SLMs) using frameworks such as PyTorch, TensorFlow, or JAX.
- Conduct experiments with supervised fine-tuning (SFT), reinforcement learning from human feedback (RLHF), and instruction tuning.
- Implement efficient training pipelines leveraging distributed training (DDP, FSDP) across GPU/TPU clusters.
- Perform hyperparameter optimisation, ablation studies, and model selection based on benchmark results.
- Develop and maintain data pipelines for collecting, cleaning, tokenising, and pre-processing large-scale training corpora.
2 Model Evaluation & Quality
- Define and implement evaluation frameworks including perplexity, BLEU, ROUGE, BERTScore, and task-specific benchmarks.
- Conduct red-teaming, bias analysis, and safety evaluations to ensure responsible AI deployment.
- Benchmark models against established baselines (e.g., GPT-2, Phi, Mistral) and track performance over iterations.
- Collaborate with QA teams to build regression suites for model versioning and continuous evaluation.
3 MLOps & Deployment
- Containerise and deploy models using Docker, Kubernetes, and cloud-native ML platforms (AWS SageMaker / GCP Vertex AI / Azure ML).
- Build and maintain model registries, experiment tracking (MLflow, Comet), and reproducible training pipelines.
- Optimise inference performance through quantisation (INT8, INT4), pruning, distillation, and ONNX/TensorRT conversion.
- Monitor model drift, data drift, and performance degradation in production; implement automated retraining triggers.
4 Research & Innovation
- Stay current with state-of-the-art NLP/LLM research; prototype and validate new techniques from published literature.
- Contribute to internal knowledge sharing, technical documentation, and model cards.
- Explore parameter-efficient fine-tuning (PEFT) methods such as LoRA, QLoRA, and Adapter layers.
- Investigate and apply mixture-of-experts (MoE), retrieval-augmented generation (RAG), and agentic workflows as needed.
5 Collaboration & Stakeholder Management
- Work with product managers and domain experts to translate business requirements into model objectives and KPIs.
- Communicate model capabilities, limitations, and trade-offs clearly to both technical and non-technical stakeholders.
- Participate in architecture reviews, sprint planning, and cross-functional design discussions.
Required Qualifications
1 Education
- Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, Statistics, or a related quantitative field.
- Equivalent professional experience with a strong portfolio of delivered AI/ML projects will be considered.
2 Experience
- 4 – 6 years of professional experience in machine learning or NLP engineering.
- Minimum 2 years of direct, hands-on experience in training or fine-tuning language models (LLMs or SLMs).
- Demonstrable experience taking a model from dataset preparation through to production deployment.
3 Technical Skills — Core
- Programming: Python (proficient); familiarity with C++/CUDA a plus.
- Deep Learning Frameworks: PyTorch (primary), TensorFlow or JAX.
- NLP Libraries: Hugging Face Transformers, Datasets, PEFT, TRL, Accelerate.
- Training Infrastructure: Multi-GPU training, FSDP, DeepSpeed ZeRO stages 1–3.
- Data Engineering: Pandas, NumPy, Apache Spark or Dask for large-scale data prep.
- Vector DBs & Retrieval: FAISS, Pinecone, Weaviate, or equivalent.
- Cloud Platforms: AWS, GCP, or Azure — ML-specific services (SageMaker, Vertex AI, etc.).
- Version Control & CI/CD: Git, GitHub/GitLab, MLflow or W&B for experiment tracking.
4 Technical Skills — Nice to Have
- Experience with multimodal models or vision-language models (VLMs).
- Knowledge of model safety, alignment techniques, and responsible AI frameworks.
- Familiarity with LangChain, LlamaIndex, or similar orchestration frameworks.
- Contributions to open-source ML projects or publications at NeurIPS, ICML, EMNLP, ACL.
Behavioural Competencies
- Intellectual Curiosity: Keeps up with rapidly evolving AI research and applies learnings pragmatically.
- Problem Solving: Approaches ambiguous problems with structured, data-driven thinking.
- Ownership: Takes full accountability for model quality, timelines, and production reliability.
- Collaboration: Works effectively in cross-functional teams with diverse skill sets.
- Communication: Distils complex technical concepts for diverse audiences.
- Adaptability: Thrives in a fast-paced environment where priorities evolve with research breakthroughs.
The Payoneer Ways of Working
Act as our customer’s partner on the inside
Learning what they need and creating what will help them go further.
Do it. Own it.
Being fearlessly accountable in everything we do.
Continuously improve
Always striving for a higher standard than our last.
Build each other up
Helping each other grow, as professionals and people.
If this sounds like a business, a community, and a mission you want to be part of, apply today.
We are committed to providing a diverse and inclusive workplace. Payoneer is an equal opportunity employer, and all qualified applicants will receive consideration for employment no matter your race, color, ancestry, religion, sex, sexual orientation, gender identity, national origin, age, disability status, protected veteran status, or any other characteristic protected by law. If you require reasonable accommodation at any stage of the hiring process, please speak to the recruiter managing the role for any adjustments. Decisions about requests for reasonable accommodation are made on a case-by-case basis.
Ready to apply?
Apply to Payoneer
Sr. Software Developer Engineer I
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Kaseya is the leading provider of AI-powered IT management and cybersecurity software, serving Managed Service Providers (MSPs) and internal IT organizations worldwide. Our comprehensive platform helps organizations efficiently manage, secure, and automate their IT environments, driving operational efficiency and long-term business success.
Backed by Insight Partners, a leading global software investor, Kaseya has experienced sustained double-digit growth and continues to expand its global footprint. Today, Kaseya supports customers in more than 20 countries and manages over 15 million endpoints worldwide.
Founded in 2000, Kaseya has built a culture centered around innovation, accountability, and results. We are a high-growth, high-performance organization that values individuals who are driven, adaptable, and committed to delivering exceptional outcomes for our customers and teammates alike.
At Kaseya, success comes from embracing challenges, moving with urgency, and continuously raising the bar.
We’re looking for Backend Engineers to lead the design and delivery of SaaS products that are powered by data, machine learning, and AI.
You’ll be the senior technical owner for one or more product areas, working across , backend, systems, and cloud infrastructure to:
- Ship high-quality data/ML/AI powered features end-to-end
- Integrate data/ML/AI capabilities into real customer workflows
- Raise the bar on design, reliability, performance, and engineering practices across the org
This is a hands-on senior role: you’ll write code, review designs, mentor senior engineers, and collaborate closely with product, design, data, and ML teams.
What You’ll Do
- Own the architecture and technical direction for key product areas in a multi-tenant SaaS platform.
- Work with product, design, and data/ML teams to translate business problems into simple, robust technical solutions.
- Drive the evolution of our system architecture (APIs, services, data flows, auth, tenancy, integrations) as the product and customer base scale.
End-to-End Full-Stack Product Delivery
- Build and maintain backend services and APIs (REST/GraphQL/gRPC) that power those experiences.
- Deliver backend features end-to-end including data schemas and business logic.
- Collaborate with UX and product to ensure responsive and delightful product experiences.
Data / ML / AI Integration
- Partner with data scientists and MLOps / platform teams to embed data, ML and AI capabilities into the product (recommendations, categorization, automation, routing, insights, LLM-powered workflows, etc.).
- Design APIs, data contracts, and UX flows that make ML/AI features reliable, understandable, and safe for customers.
- Ensure telemetry and feedback loops are in place so data/ML teams can measure performance, iterate models, and improve outcomes.
- Help define and implement guardrails for AI features (fallbacks, explanations, error handling, permissions).
Operational Excellence
- Champion operability: monitoring, alerting, logging, and runbooks for services you own.
- Lead efforts to improve performance, scalability, and resilience of critical paths (e.g., onboarding, reporting, AI-assisted workflows).
- Work with security and compliance to ensure features meet requirements around authentication, authorization, data privacy, and multi-tenancy.
- Participate in and help evolve on-call / incident response processes as a technical leader.
Engineering Excellence & Leadership
- Act as a technical mentor for multiple teams, raising the bar on code quality, reviews, testing, and design.
- Lead technical design reviews and cross-team architecture discussions, especially where product, data, and ML intersect.
- Help define engineering standards and best practices (API design, frontend patterns, error handling, observability, testing).
- Partner with engineering management to shape roadmaps, staffing, and sequencing for major initiatives.
What You’ll Bring
Experience
- 10+ years of software engineering experience
- Demonstrated experience shipping data/ML/AI powered SaaS products,
- Strong track record of owning and shipping complex, user-facing features end-to-end in collaboration with product management and UX.
- Experience as a senior member of the technical staff in guiding teams and owning critical production systems.
Technical Skills
- Strong proficiency with at least one backend stack, for example:
- Node.js/TypeScript, Java, Go, Rust, or similar
- Designing and building APIs, services, and integrations
- Proficiency with Python and data analysis/modeling tools (e.g. pandas/pytorch)
- Solid understanding of data modeling and storage: relational databases, caching, and basic data warehousing concepts.
- Familiarity with data/ML/AI concepts:
- How ML models or LLMs are exposed as services
- Typical failure modes, latency/throughput considerations, and guardrails
- Experience with cloud platforms (AWS / GCP / Azure), containers, and infrastructure (networking, scaling, security).
- Strong habits around testing, CI/CD, code reviews, and incremental delivery.
Mindset & Soft Skills
- Product-minded engineer who cares about customer problems, usability, and outcomes, not just code.
- Systems thinker who can balance short-term delivery with long-term architectural health.
- Excellent communicator, comfortable driving alignment across engineering, product, data, and go-to-market teams.
- Enjoys mentoring and multiplying the impact of other engineers.
Additional information
Kaseya provides equal employment opportunity to all employees and applicants without regard to race, religion, age, ancestry, gender, sex, sexual orientation, national origin, citizenship status, physical or mental disability, veteran status, marital status, or any other characteristic protected by applicable law.
Ready to apply?
Apply to Kaseya Careers
Application Architect
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Role Overview:
We are looking for a hands-on Product Architect / Engineer to design and build an AI-driven operations platform focused on intelligent automation, insights, and optimization across cloud, network, and application operations.This role blends product thinking, architecture, and deep engineering across AI/ML and Agentic AI systems.
Key Responsibilities:
- Architect and build the agentic AI platform leveraging AI, ML, and Agentic AI frameworks
- Design multi-agent systems for use cases for operations domains like Cloud Ops, NetworkOps, ServiceDesk, root cause analysis, anomaly detection, and predictive insights
- Develop data pipelines and telemetry fabric for ingesting and processing large-scale operational data (logs, metrics, traces, topology)
- Build and integrate LLM-powered copilots and autonomous agents for operations
- Define product architecture, including microservices, APIs, event-driven systems, and scalable cloud-native patterns
- Translate business needs into AI-driven product features and accelerators
- Collaborate with product, operations, and engineering teams to deliver end-to-end capabilities
Key Skills:
- Strong experience in product architecture and full-stack engineering
- Hands-on expertise in:
- AI/ML (model development, inference, MLOps)
- LLMs and Agentic AI frameworks (multi-agent orchestration, reasoning systems)
- Data engineering (streaming, batch, real-time analytics)
- Proficiency in Python and modern frameworks
- Experience with cloud platforms (AWS, Azure) and cloud-native architecture
- Agent framework experience – Microsoft agent framework, langgraph and langchain.
- Strong understanding of:
- Observability systems (logs, metrics, traces)
- AIOps / IT operations platforms
- API design and microservices architecture
- Familiarity with vector databases, embeddings, RAG architectures, and knowledge graphs
Good to Have:
- Experience building autonomous AI agents for IT/network/application operations
- Exposure to FinOps, Cloud Cost Optimization,
- Knowledge of network topology, infrastructure ops, or ITSM tools
- Experience with real-time decisioning systems and event correlation engines
Ready to apply?
Apply to Orion Innovation Naukri
Sr.MTS - Software Development
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Who We Are:
Aviatrix® is pioneering the Cloud Native Security Fabric — the architecture the Containment Era requires. The Cloud Native Security Fabric governs every workload communication path across every cloud, every VPC, every Kubernetes cluster, and every serverless function, from a single policy plane. One rule. Universal propagation. Enforced at the workload, not at a chokepoint. Trusted by more than 500 of the world's leading enterprises. For more information, visit aviatrix.ai.
About the Role – Senior Member of Technical Staff – Software Development
Our SaaS platform serves enterprise customers with a reliable, secure, and scalable product built on modern microservices, event-driven data pipelines, and AI-powered capabilities.We are seeking a Senior Member of Technical Staff (Sr MTS) – Software Development to join our SaaS Platform team. This role is ideal for a backend engineer who has moved beyond writing individual features and is ready to take meaningful ownership of platform components, contribute to technical design, and start influencing the direction of the team. You will work alongside Staff and Principal Engineers on building microservices, data pipelines, and AI-integrated backend systems on AWS — developing both your technical depth and your ability to lead within a team.
Position Responsibilities:
Feature Development & Ownership
- Take end-to-end ownership of backend features and services — from requirements and design through implementation, testing, deployment, and monitoring.
- Design and implement production-grade microservices in Golang, following team standards for gRPC and RESTful API patterns.
- Contribute meaningfully to technical design discussions; author design documents for features and components you own, incorporating feedback from senior engineers.
- Write well-tested, maintainable code; champion testing practices including unit, integration, and end-to-end tests within your feature area.
- Participate in on-call rotations; debug and resolve issues in distributed backend services and contribute to post-incident reviews.
Data Pipelines & AI Integration
- Build and extend data pipeline components that process, enrich, and route platform telemetry and events using AWS streaming and batch services (Kinesis, MSK, Glue, Step Functions).
- Integrate AI and LLM capabilities into backend services and pipeline stages — including model inference calls, output parsing, and result handling — under the guidance of Staff Engineers.
- Implement agentic AI workflow components such as tool-use handlers, retrieval-augmented generation (RAG) steps, and prompt orchestration layers as part of broader pipeline designs.
- Contribute to the reliability and correctness of AI pipeline components through thorough testing, output validation, and adherence to team guardrail standards.
Platform Reliability & Operations
- Ensure backend services you build are observable from day one: structured logging, metrics, distributed tracing, and alerting are treated as part of the definition of done.
- Apply AWS networking and security best practices in the services you build: secure IAM roles, VPC-aware service communication, and encryption in transit and at rest.
- Proactively identify and address reliability gaps, performance bottlenecks, and technical debt in platform components you own.
- Support deployment of services on AWS using team CI/CD pipelines and infrastructure-as-code tooling.
Collaboration & Team Contribution
- Collaborate effectively with Staff and Principal Engineers, product managers, and peers across a geographically distributed team.
- Conduct thorough code reviews and provide constructive, actionable feedback; help MTS engineers grow through mentorship on your area of expertise.
- Document APIs, service behavior, data flows, and runbooks clearly so teammates can understand, operate, and evolve your work.
- Participate actively in planning, estimation, and sprint ceremonies; raise technical risks and dependencies early.
Requirements
Experience & Education
- 3+ years of professional software engineering experience in backend development.
- Bachelor’s degree in Computer Science, Engineering, or a related technical field (or equivalent practical experience).
- Solid foundation in computer science fundamentals: data structures, algorithms, and operating systems.
- Demonstrated experience owning and shipping backend features or services in a production cloud environment.
- Experience working in collaborative, agile engineering teams; comfortable operating in fast-paced, high-growth environments.
Backend & Microservices
- Proficiency in Golang or a comparable strongly typed backend language; willingness to work primarily in Golang.
- Working understanding of microservices architecture: service boundaries, inter-service communication via REST and gRPC, and the trade-offs of distributed systems.
- Experience designing and implementing APIs with attention to correctness, reliability, and ease of use by other services.
- Familiarity with event-driven patterns and messaging systems such as Kafka, Kinesis, or SQS/SNS.
- Strong testing practices: unit, integration, and contract testing for backend services.
Agentic AI & LLM Integration
- Working knowledge of large language models (LLMs) and how they are integrated into backend systems via API calls (e.g., Amazon Bedrock, OpenAI, or Anthropic APIs).
- Familiarity with agentic AI concepts: tool use, multi-step reasoning, and agent orchestration frameworks such as LangChain, LlamaIndex, or Amazon Bedrock Agents.
- Ability to implement prompt templates, manage context windows, and handle model outputs reliably within backend service logic.
- Understanding of retrieval-augmented generation (RAG) patterns: embedding generation, vector store queries, and context injection into prompts.
- Awareness of production considerations for AI components: output validation, error handling, latency management, and cost awareness.
Data Pipelines
- Practical experience building or contributing to data pipelines for real-time or batch processing workloads.
- Familiarity with AWS data pipeline services: Amazon Kinesis, AWS Glue, Amazon MSK (Kafka), AWS Step Functions, or Amazon EMR.
- Understanding of how to embed AI/ML model inference calls as processing steps within a data pipeline.
- Ability to add pipeline observability: tracking throughput, latency, error rates, and data quality metrics.
AWS & Cloud Infrastructure
- Hands-on experience deploying and operating backend services on AWS; familiarity with core services including EC2, ECS/EKS, S3, RDS, and SQS/SNS.
- Basic understanding of AWS networking and security: VPC, security groups, IAM roles and policies, and encrypted communications.
- Experience with containerization (Docker) and deploying services in container-based environments.
- Comfort working with CI/CD pipelines, Git-based workflows, and infrastructure-as-code tooling (Terraform or AWS CDK is a plus).
Nice to Have
- Experience with Kubernetes (EKS) for container orchestration.
- Hands-on use of Amazon Bedrock or equivalent managed AI platforms for LLM inference.
- Experience with vector databases or embedding stores (OpenSearch, pgvector, Pinecone).
- Exposure to AWS managed data services such as Amazon Redshift, DynamoDB, or Aurora.
- Background in network security, cloud networking, or multi-cloud environments.
- Interest in or exposure to ML model lifecycle management and MLOps practices.
Interpersonal & Communication
- Clear written and verbal communication; able to write design documents, articulate technical decisions, and give constructive code review feedback.
- Collaborative team player who works well in cross-functional, geographically distributed teams.
- A growth mindset — eager to deepen expertise, take on new challenges, and mentor peers as you develop.
BENEFITS
US: We cover 100% of employee premiums and 88% of dependent(s) premiums for medical, dental and vision coverage, 401(k) match, short and long-term disability, life/AD&D insurance, $1,000/year education reimbursement, and a flexible vacation policy.
Outside the US: We offer a comprehensive benefits package which, (subject to regional variations) could include pension, private medical for you and dependents, generous holiday allowance, life assurance, long-term disability, annual wellbeing stipend
Your total compensation package will be based on job-related knowledge, education, certifications and location, per our aligned ranges.
About Aviatrix
Aviatrix® is the cloud network security company trusted by more than 500 of the world’s leading enterprises. As cloud infrastructures become more complex and costly, the Aviatrix Cloud Network Security platform gives companies back the power, control, security, and simplicity they need to modernize their cloud strategies. Aviatrix is the only secure networking solution built specifically for the cloud, that ensures companies are ready for AI and what’s next. Combined with the Aviatrix Certified Engineer (ACE) Program, the industry’s leading secure multicloud networking certification, Aviatrix unifies cloud, networking, and security teams and unlocks greater potential across any cloud.
WE WANT TO INCLUDE YOU
We embrace the fact that not everyone’s journey took the same route or started at the same place. If your experience doesn’t quite meet the requirements but the opportunity excites you and you believe you could be great, don’t let that hold you back from applying. Tell us what you CAN bring and what makes you special.
Aviatrix is a community where everyone's career can grow and we want to help you achieve your goals and be “your best YOU,” however that looks. If you're seeking an opportunity where you can be excited to start work every morning with enthusiastic people, make a real difference and be part of something amazing then let’s talk. We want to get to know you and how we could grow together.
Aviatrix, Inc. is an equal opportunity employer and does not make hiring decisions based on race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.
CPRA - California Applicant Privacy Notice
Ready to apply?
Apply to Aviatrix
Senior Machine Learning Engineer
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What Cognite is: Relentless to achieve
Cognite operates at the forefront of industrial digitalization, building AI, and data solutions that solve the world’s hardest, highest-impact problems. With unmatched industrial heritage and a comprehensive suite of AI capabilities, including low-code AI agents, Cognite accelerates the digital transformation to drive operational improvements.
We thrive in challenges. We challenge assumptions. We execute with speed and ownership. If you view obstacles as signals to step forward - not backwards - you’ll feel right at home here.
Our Moonshot is bold: Unlock $100B in customer value by 2035, and redefine how global industry works. Join us in this venture where AI and data meet ingenuity, and together, we will forge the path to a smarter, more connected industrial future.
About the Opportunity
We are building the next generation of contextual AI for Industrial Operations. Our team focuses on transforming unstructured, complex industrial data—ranging from technical manuals to complex piping and instrumentation diagrams (P&IDs)—into structured, actionable intelligence. We leverage state-of-the-art Deep Learning, Generative AI, and Computer Vision to drive efficiency, safety, and operational excellence.
About the Role
As a Senior Machine Learning Engineer, you will be the engine of our contextualization initiatives, taking independent ownership of complex ML features from conception to production. You will bridge the gap between data science and software engineering, building the models and the surrounding infrastructure that parse complex industrial documents, extract multimodal entities, and interpret intricate engineering diagrams.
To be clear: this is an engineering-first role. We are not just looking for researchers to build isolated models; we need builders who write production-grade code, build robust APIs, and solve complex infrastructure problems. You will treat ML models as software components integrated into a highly scalable archite
How you’ll demonstrate Ownership- System-minded, focused on maintainability, rigorous testing, and automated pipelines for reliable ML production.
- Thrives in ambiguity, independently defining the technical path, selecting tools judiciously, and driving solutions to completion.
- Elevates team code quality through constructive reviews and informal mentorship, bridging the gap between research and production
The Impact you bring to Cognite
Key Responsibilities
- Take product requirements and independently design, train, test, and deploy ML models (e.g., NLP, Vision-Language Models) for document parsing, layout analysis, and entity matching.
- Write high-quality, scalable production code (Python). Wrap your ML models into robust RESTful or gRPC APIs and integrate them seamlessly into existing industrial master data systems and workflows.
- Implement and maintain CI/CD pipelines for your models. Navigate complex deployment environments, manage containerized applications (Docker/Kubernetes), and optimize inference bottlenecks.
- Work with Principal engineers to translate high-level system architectures into concrete, scalable data pipelines and production-ready microservices.
- Design automated testing for ML pipelines. Monitor deployed models in production for data drift, latency, and accuracy, proactively implementing retraining strategies.
- Collaborate effectively with product managers to define ML capabilities. Provide code reviews and informal technical mentorship to engineers.
Required Skills and Qualifications
- Bachelor’s or Master's degree in Computer Science, Data Science, Software Engineering, or a related field.
- 6–10 years of industry experience in software engineering with a strong focus on machine learning, MLOps, and API development.
- Strong programming skills in Python with experience using backend web frameworks (e.g., FastAPI, Flask, Django) to serve models.
- Solid expertise in frameworks like PyTorch, TensorFlow, Hugging Face Transformers, or LangChain.
- Hands-on experience with containerization (Docker, Kubernetes), Linux environments, CI/CD tools (GitHub Actions, Jenkins), and deploying models on cloud platforms (AWS, Azure, or GCP).
- Solid understanding of software architecture, data structures, and algorithms to ensure performant code.
- Hands-on experience with distributed data processing frameworks (e.g., Apache Spark, Ray, Dask) and orchestrating complex data workflows (e.g., Apache Airflow, Dagster, Prefect).
What Sets your Role Apart
- Independently define the technical ML/SWE approach for ambiguous feature requests and deliver to production.
- Recognize the model is a small part of the solution; expertly manage aspects like API rate limiting, asynchronous processing, and robust data routing around ML components.
- Possess hands-on experience maintaining production ML models and designing resilient systems against poor data quality..
Preferred Qualifications
- Proven experience fine-tuning and deploying multimodal models for visual data and engineering diagrams in live environments.
- Built robust, production-grade RAG pipelines, expertly utilizing Vector/Graph Databases for high-accuracy entity retrieval.
- Familiar with orchestrating multi-step reasoning using frameworks like LangGraph or AutoGen for real-world problem-solving.
- Strong understanding of advanced OCR, layout parsing, and techniques for consistent structured JSON extraction from complex industrial PDFs. Manufacturing/OT dataset experience preferred.
- Ability to optimize LLMs/VLMs for inference latency (quantization, TensorRT, vLLM), potentially in constrained, on-premises environments.
- Experience with modern data lake/lakehouse architectures (Delta Lake, Iceberg, Databricks) for efficient querying and preprocessing of petabyte-scale unstructured data for LLM/VLM training and RAG.
- Impact 2025
- Cognite's Industrial AI: Moonshot
- We’re globally recognized domain experts with an international presence that spans Phoenix, Houston, Oslo Tokyo, Bengaluru, and Abu Dhabi.
Ready to apply?
Apply to Cognite - AI for Industry
WHO WE ARE:
Zinnia is the leading technology platform for accelerating life and annuities growth. With innovative enterprise solutions and data insights, Zinnia simplifies the experience of buying, selling, and administering insurance products. All of which enables more people to protect their financial futures. Our success is driven by a commitment to three core values: be bold, team up, deliver value – and that we do. Zinnia has over $180 billion in assets under administration, serves 100+ carrier clients, 2500 distributors and partners, and over 2 million policyholders.
WHO YOU ARE
You are a passionate Python and AI/ML Engineer minimum 4 years of hands-on experience building intelligent systems. You thrive in fast-paced environments, love solving complex problems with data and algorithms, and take pride in delivering AI solutions that create real business impact. You have experience with cutting-edge Generative AI, scalable ML pipelines, and production-grade systems and you're energized by working at the frontier of what AI can do.
WHAT YOU'LL DO
- Design, develop, and deploy machine learning models and Generative AI solutions — including classification, clustering, summarization, search & ranking, and information extraction.
- Own end-to-end ML pipelines — from data ingestion and preprocessing through model training, deployment, and production monitoring.
- Collaborate with cross-functional teams to translate business requirements into AI-driven features — applying NLP, outlier detection, and deep learning techniques where applicable.
- Build robust, scalable, and well-documented Python-based RESTful APIs to expose ML models and AI services in production environments.
- Optimize database interactions and ensure efficient data storage and retrieval for AI applications across SQL and NoSQL systems.
- Stay current with the latest advances in AI/ML — integrating emerging approaches such as RAG pipelines, LLM fine-tuning, and vector search into live products.
WHAT YOU'LL NEED
Python
Strong hands-on proficiency for building, scripting, and deploying AI/ML systems.
NumPy · Pandas · FastAPI · Scikit-learn
Machine Learning
Applied expertise across supervised, unsupervised, and deep learning — classification, clustering, outlier detection.
PyTorch · TensorFlow · XGBoost · DBSCAN
Generative AI (2+ yrs)
Hands-on experience building with LLMs — prompt engineering, RAG pipelines, summarization, and AI-powered features.
LLMs · RAG · Prompt Eng. · Fine-tuning
NLP & Search / Ranking
Processes language and builds relevance engines — NER, embeddings, semantic search, and ranking models.
spaCy · BERT · FAISS · Elasticsearch
API Development
Designs and ships secure, well-documented RESTful APIs exposing ML models as production-ready services.
REST · FastAPI · OAuth2 · Swagger
Databases
Proficient in SQL and NoSQL stores for structured and unstructured data pipelines supporting AI workloads.
PostgreSQL · MongoDB · Vector DBs
GOOD TO HAVE
Cloud Platforms
Deploys and scales AI workloads on AWS, Azure, or GCP.
AWS · Azure
TypeScript / JavaScript
Frontend or full-stack exposure for building ML-powered product interfaces.
TypeScript · React · Node.js
MLOps
Manages the ML lifecycle — tracking, versioning, and pipeline automation.
MLflow · Kubeflow · CI/CD
Containerization & Orchestration
Packages and scales AI services using containers and cluster management.
Docker · Kubernetes
Ready to apply?
Apply to Zinnia
Who We Are & Why Join Us
Avathon is the only physical AI unicorn headquartered in the San Francisco Bay Area, we go beyond models and dashboards we deploy AI that continuously computes across supply chains, energy systems, and industrial operations. Our Operational Technology platform turns fragmented data into real-time, autonomous decisioning across the systems that power the global economy.
This is not digital AI. This is AI for operational reality where latency, constraints, and failure have real-world consequences.
Cutting-Edge AI Innovation – Join a team at the forefront of AI, developing groundbreaking solutions that shape the future.
High-Growth Environment – Thrive in a fast-scaling startup where agility, collaboration, and rapid professional growth are the norm.
Meaningful Impact – Work on AI-driven projects that drive real change across industries and improve lives.
Learn more at: Avathon
Staff Data Scientist – Supply Chain AI (Small Language Models)
At Avathon, we build AI products that solve real industrial problems at scale. We believe the future of enterprise AI lies in small, focused, high-performance models—deeply grounded in domain context—not just large, generic systems.
We’re looking for an experienced Data Scientist to join our Supply Chain AI team in India. In this role, you’ll design, fine-tune, and deploy optimized Small Language Models (SLMs) that power production-grade AI features across logistics, planning, inventory, and demand forecasting.
What Makes This Role Unique
This is a product-first data science role. You won’t just build models—you’ll own how they show up in real products used by large enterprises. Your work becomes the intelligence layer that sits on top of our graph and indexing systems and directly drives customer outcomes.
What You’ll Do
- Build and fine-tune SLMs/LLMs for production use cases such as semantic search, forecasting, contract intelligence, and conversational insights. Optimize models for performance, cost, and latency using PEFT, quantization, and efficient inference techniques
- Embed supply chain knowledge into models by working closely with domain experts and product teams
- Enable agentic workflows, allowing AI Assistants to execute planning, optimization, and decision-support tasks
- Integrate models into products using custom Lambdas, and a Graph-based microservices architecture
- Apply vector search and semantic reasoning to help customers navigate complex supply chain relationships
- Work with real enterprise data—ERP, logistics, inventory, supplier, and contract datasets
- Deploy and operate models using strong MLOps practices on platforms like AWS, GCP or AZURE
- Measure and improve quality, reducing hallucinations and improving reliability through continuous evaluation
- Partner with engineering, product, and operations teams to ship impactful AI features end-to-end
What We’re Looking For
- Experience working with SLMs (Mistral, Phi, Nemotron, Llama variants), applying parameter-efficient fine-tuning (LoRA/QLoRA) to optimize task-specific natural language query answering with high accuracy and minimized hallucinations.
- Strong understanding of supply chain data and workflows (logistics, inventory, procurement, ERP systems)
- Familiarity with Knowledge Graphs and graph-based data modeling, including designing and querying Neo4j graphs for relationship-driven insights.
- Solid hands-on skills in Python, PyTorch/TensorFlow, GraphQL, and vector databases
- 8+ years of experience in forecasting, optimization, supply chain analytics, or AI-driven products
- Experience designing Retrieval-Augmented Generation pipelines using document chunking, metadata filtering, hybrid (dense + sparse) retrieval, and SLM/LLM grounding for enterprise knowledge search.
- Hands-on experience building and tuning FAISS-based vector indexes (IVF, HNSW, PQ) for large-scale semantic similarity search with low-latency production deployment
- Experience taking models from prototype to production
- Bonus: reinforcement learning, MARL, graph neural networks, or probabilistic modeling
- Clear communication skills and a strong sense of product ownership
Why Avathon
You’ll work on core AI products, not experiments—solving complex supply chain problems for global enterprises, while building from India as a key innovation hub.
If you enjoy shipping AI that delivers measurable business value, this role is for you.
Avathon is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, pregnancy, genetic information, disability, status as a protected veteran, or any other protected category under applicable federal, state, and local laws.
Avathon is committed to providing reasonable accommodations throughout the recruiting process. If you need a reasonable accommodation, please contact us to discuss how we can assist you.
Ready to apply?
Apply to Avathon
The salary range for this role is $50,000 - $120,000 per year (Gross in USD)
About Sezzle:
With a mission to financially empower the next generation, Sezzle is revolutionizing the shopping experience beyond payments, blending cutting-edge tech with seamless, interest-free installment plans that make shopping smarter and more accessible. We’re not just transforming payments; we’re redefining how people discover, interact with, and purchase the things they love while driving real impact on merchant sales through increased conversions and higher order values. As we continue to shape the future of fintech and retail, we’re building an innovative, dynamic team passionate about creating more than just a transaction but a truly unique shopping journey. If you’re excited about pushing boundaries in tech and delivering a game-changing experience for consumers and merchants alike, come join us at Sezzle and help create the future of shopping!
About the Role:
We are seeking a talented and motivated Sr. AI engineer who is best in class with a high IQ plus a high EQ. This role presents an exciting opportunity to thrive in a dynamic, fast-paced environment within a rapidly growing team, with abundant prospects for career advancement.
You will be responsible for overseeing the design, development, and deployment of machine learning models that power and enhance our financial platform. In this role, you will drive the creation of scalable machine learning solutions for personalized recommendations in the Sezzle marketplace, fraud detection, and credit risk assessment, utilizing a combination of cloud services, open-source tools, and proprietary algorithms.
Your leadership will be key in blending machine learning development and operations (MLOps) to automate and optimize the full lifecycle of our ML models. You will collaborate with a team of engineers and data scientists to build large-scale, high-quality solutions that address diverse challenges in the shopping and fintech space. You’ll ensure our AI-driven features are robust, efficient, and scalable as we continue to grow.
What You'll Do:
- Design, Build, and Maintain Scalable ML Infrastructure: Lead the design and development of scalable machine learning infrastructure on AWS, utilizing services like AWS Sagemaker for efficient model training and deployment.
- Collaborate with Product Teams: Work closely with product teams to develop MVPs for AI-driven features, ensuring quick iterations and market testing to refine solutions effectively.
- Develop Monitoring & Alerting Frameworks: Create and enhance monitoring and alerting systems for machine learning models to ensure high performance, reliability, and minimal downtime.
- Support Cross-Departmental AI Utilization: Enable various departments within the organization to leverage AI/ML models, including cutting-edge Generative AI solutions, for different use cases.
- Provide Production Support: Offer expertise in debugging and resolving issues related to machine learning models in production, participating in on-call rotations for operational troubleshooting and incident resolution.
- Scale ML Architecture: Design and scale machine learning architecture to support rapid user growth, leveraging deep knowledge of AWS and ML best practices to ensure robustness and efficiency.
- Mentor and Elevate Team Skills: Conduct code reviews, mentor team members, and elevate overall team capabilities through knowledge sharing and collaboration.
- Stay Ahead of the Curve: Stay updated with the latest advancements in machine learning technologies and AWS services, driving the adoption of cutting-edge solutions to maintain a competitive edge.
What We Look For:
- Bachelor's degree in Computer Science, Computer Engineering, Machine Learning, Statistics, Physics, or a relevant technical field, or equivalent practical experience.
- At least 6+ years of experience in machine learning engineering, with demonstrated success in deploying scalable ML models in a production environment.
Preferred Qualifications:
- Deep expertise in one or more of the following areas: machine learning, recommendation systems, pattern recognition, data mining, artificial intelligence, or related technical fields.
- Proven track record of developing machine learning models from inception to business impact, demonstrating the ability to solve complex challenges with innovative solutions.
- Proficiency with Python is required, and experience with Golang is a plus.
- Demonstrated technical leadership in guiding teams, owning end-to-end projects, and setting the technical direction to achieve project goals efficiently.
- Experience working with relational databases, data warehouses, and using SQL to explore them.
- Strong familiarity with AWS cloud services, especially in deploying and managing machine learning solutions and scaling them in a cost-effective manner.
- Knowledgeable in Kubernetes, Docker, and CI/CD pipelines for efficient deployment and management of ML models.
- Comfortable with monitoring and observability tools tailored for machine learning models (e.g., Prometheus, Grafana, AWS CloudWatch) and experienced in developing recommender systems or enhancing user experiences through personalized recommendations.
- Solid foundation in data processing and pipeline frameworks (e.g., Apache Spark, Kafka) for handling real-time data streams.
About You:
- You have relentlessly high standards - many people may think your standards are unreasonably high. You are continually raising the bar and driving those around you to deliver great results. You make sure that defects do not get sent down the line and that problems are fixed so they stay fixed.
- You’re not bound by convention - your success—and much of the fun—lies in developing new ways to do things
- You need action - speed matters in business. Many decisions and actions are reversible and do not need extensive study. We value calculated risk-taking.
- You earn trust - you listen attentively, speak candidly, and treat others respectfully.
- You have backbone; disagree, then commit - you can respectfully challenge decisions when you disagree, even when doing so is uncomfortable or exhausting. You have conviction and are tenacious. You do not compromise for the sake of social cohesion. Once a decision is determined, you commit wholly.
- You deliver results - you focus on the key inputs and deliver them with the right quality and in a timely fashion. Despite setbacks, you rise to the occasion and never settle.
What Makes Working at Sezzle Awesome:
At Sezzle, we are more than just brilliant engineers, passionate data enthusiasts, out-of-the-box thinkers, and determined innovators. We believe in surrounding ourselves with only the best and the brightest individuals. Our culture is not defined by a certain set of perks designed to give the illusion of the traditional startup culture, but rather, it is the visible example living in every employee that we hire.
#Li-remote #full-time
Ready to apply?
Apply to SezzleThe salary range for this role is $50,000 - $120,000 per year (Gross in USD)
About Sezzle:
With a mission to financially empower the next generation, Sezzle is revolutionizing the shopping experience beyond payments, blending cutting-edge tech with seamless, interest-free installment plans that make shopping smarter and more accessible. We’re not just transforming payments; we’re redefining how people discover, interact with, and purchase the things they love while driving real impact on merchant sales through increased conversions and higher order values. As we continue to shape the future of fintech and retail, we’re building an innovative, dynamic team passionate about creating more than just a transaction but a truly unique shopping journey. If you’re excited about pushing boundaries in tech and delivering a game-changing experience for consumers and merchants alike, come join us at Sezzle and help create the future of shopping!
About the Role:
We are seeking a talented and motivated Sr. AI engineer who is best in class with a high IQ plus a high EQ. This role presents an exciting opportunity to thrive in a dynamic, fast-paced environment within a rapidly growing team, with abundant prospects for career advancement.
You will be responsible for overseeing the design, development, and deployment of machine learning models that power and enhance our financial platform. In this role, you will drive the creation of scalable machine learning solutions for personalized recommendations in the Sezzle marketplace, fraud detection, and credit risk assessment, utilizing a combination of cloud services, open-source tools, and proprietary algorithms.
Your leadership will be key in blending machine learning development and operations (MLOps) to automate and optimize the full lifecycle of our ML models. You will collaborate with a team of engineers and data scientists to build large-scale, high-quality solutions that address diverse challenges in the shopping and fintech space. You’ll ensure our AI-driven features are robust, efficient, and scalable as we continue to grow.
What You'll Do:
- Design, Build, and Maintain Scalable ML Infrastructure: Lead the design and development of scalable machine learning infrastructure on AWS, utilizing services like AWS Sagemaker for efficient model training and deployment.
- Collaborate with Product Teams: Work closely with product teams to develop MVPs for AI-driven features, ensuring quick iterations and market testing to refine solutions effectively.
- Develop Monitoring & Alerting Frameworks: Create and enhance monitoring and alerting systems for machine learning models to ensure high performance, reliability, and minimal downtime.
- Support Cross-Departmental AI Utilization: Enable various departments within the organization to leverage AI/ML models, including cutting-edge Generative AI solutions, for different use cases.
- Provide Production Support: Offer expertise in debugging and resolving issues related to machine learning models in production, participating in on-call rotations for operational troubleshooting and incident resolution.
- Scale ML Architecture: Design and scale machine learning architecture to support rapid user growth, leveraging deep knowledge of AWS and ML best practices to ensure robustness and efficiency.
- Mentor and Elevate Team Skills: Conduct code reviews, mentor team members, and elevate overall team capabilities through knowledge sharing and collaboration.
- Stay Ahead of the Curve: Stay updated with the latest advancements in machine learning technologies and AWS services, driving the adoption of cutting-edge solutions to maintain a competitive edge.
What We Look For:
- Bachelor's degree in Computer Science, Computer Engineering, Machine Learning, Statistics, Physics, or a relevant technical field, or equivalent practical experience.
- At least 6+ years of experience in machine learning engineering, with demonstrated success in deploying scalable ML models in a production environment.
Preferred Qualifications:
- Deep expertise in one or more of the following areas: machine learning, recommendation systems, pattern recognition, data mining, artificial intelligence, or related technical fields.
- Proven track record of developing machine learning models from inception to business impact, demonstrating the ability to solve complex challenges with innovative solutions.
- Proficiency with Python is required, and experience with Golang is a plus.
- Demonstrated technical leadership in guiding teams, owning end-to-end projects, and setting the technical direction to achieve project goals efficiently.
- Experience working with relational databases, data warehouses, and using SQL to explore them.
- Strong familiarity with AWS cloud services, especially in deploying and managing machine learning solutions and scaling them in a cost-effective manner.
- Knowledgeable in Kubernetes, Docker, and CI/CD pipelines for efficient deployment and management of ML models.
- Comfortable with monitoring and observability tools tailored for machine learning models (e.g., Prometheus, Grafana, AWS CloudWatch) and experienced in developing recommender systems or enhancing user experiences through personalized recommendations.
- Solid foundation in data processing and pipeline frameworks (e.g., Apache Spark, Kafka) for handling real-time data streams.
About You:
- You have relentlessly high standards - many people may think your standards are unreasonably high. You are continually raising the bar and driving those around you to deliver great results. You make sure that defects do not get sent down the line and that problems are fixed so they stay fixed.
- You’re not bound by convention - your success—and much of the fun—lies in developing new ways to do things
- You need action - speed matters in business. Many decisions and actions are reversible and do not need extensive study. We value calculated risk-taking.
- You earn trust - you listen attentively, speak candidly, and treat others respectfully.
- You have backbone; disagree, then commit - you can respectfully challenge decisions when you disagree, even when doing so is uncomfortable or exhausting. You have conviction and are tenacious. You do not compromise for the sake of social cohesion. Once a decision is determined, you commit wholly.
- You deliver results - you focus on the key inputs and deliver them with the right quality and in a timely fashion. Despite setbacks, you rise to the occasion and never settle.
What Makes Working at Sezzle Awesome:
At Sezzle, we are more than just brilliant engineers, passionate data enthusiasts, out-of-the-box thinkers, and determined innovators. We believe in surrounding ourselves with only the best and the brightest individuals. Our culture is not defined by a certain set of perks designed to give the illusion of the traditional startup culture, but rather, it is the visible example living in every employee that we hire.
#Li-remote #full-time
Ready to apply?
Apply to SezzleThe salary range for this role is $50,000 - $120,000 per year (Gross in USD)
About Sezzle:
With a mission to financially empower the next generation, Sezzle is revolutionizing the shopping experience beyond payments, blending cutting-edge tech with seamless, interest-free installment plans that make shopping smarter and more accessible. We’re not just transforming payments; we’re redefining how people discover, interact with, and purchase the things they love while driving real impact on merchant sales through increased conversions and higher order values. As we continue to shape the future of fintech and retail, we’re building an innovative, dynamic team passionate about creating more than just a transaction but a truly unique shopping journey. If you’re excited about pushing boundaries in tech and delivering a game-changing experience for consumers and merchants alike, come join us at Sezzle and help create the future of shopping!
About the Role:
We are seeking a talented and motivated Sr. AI engineer who is best in class with a high IQ plus a high EQ. This role presents an exciting opportunity to thrive in a dynamic, fast-paced environment within a rapidly growing team, with abundant prospects for career advancement.
You will be responsible for overseeing the design, development, and deployment of machine learning models that power and enhance our financial platform. In this role, you will drive the creation of scalable machine learning solutions for personalized recommendations in the Sezzle marketplace, fraud detection, and credit risk assessment, utilizing a combination of cloud services, open-source tools, and proprietary algorithms.
Your leadership will be key in blending machine learning development and operations (MLOps) to automate and optimize the full lifecycle of our ML models. You will collaborate with a team of engineers and data scientists to build large-scale, high-quality solutions that address diverse challenges in the shopping and fintech space. You’ll ensure our AI-driven features are robust, efficient, and scalable as we continue to grow.
What You'll Do:
- Design, Build, and Maintain Scalable ML Infrastructure: Lead the design and development of scalable machine learning infrastructure on AWS, utilizing services like AWS Sagemaker for efficient model training and deployment.
- Collaborate with Product Teams: Work closely with product teams to develop MVPs for AI-driven features, ensuring quick iterations and market testing to refine solutions effectively.
- Develop Monitoring & Alerting Frameworks: Create and enhance monitoring and alerting systems for machine learning models to ensure high performance, reliability, and minimal downtime.
- Support Cross-Departmental AI Utilization: Enable various departments within the organization to leverage AI/ML models, including cutting-edge Generative AI solutions, for different use cases.
- Provide Production Support: Offer expertise in debugging and resolving issues related to machine learning models in production, participating in on-call rotations for operational troubleshooting and incident resolution.
- Scale ML Architecture: Design and scale machine learning architecture to support rapid user growth, leveraging deep knowledge of AWS and ML best practices to ensure robustness and efficiency.
- Mentor and Elevate Team Skills: Conduct code reviews, mentor team members, and elevate overall team capabilities through knowledge sharing and collaboration.
- Stay Ahead of the Curve: Stay updated with the latest advancements in machine learning technologies and AWS services, driving the adoption of cutting-edge solutions to maintain a competitive edge.
What We Look For:
- Bachelor's degree in Computer Science, Computer Engineering, Machine Learning, Statistics, Physics, or a relevant technical field, or equivalent practical experience.
- At least 6+ years of experience in machine learning engineering, with demonstrated success in deploying scalable ML models in a production environment.
Preferred Qualifications:
- Deep expertise in one or more of the following areas: machine learning, recommendation systems, pattern recognition, data mining, artificial intelligence, or related technical fields.
- Proven track record of developing machine learning models from inception to business impact, demonstrating the ability to solve complex challenges with innovative solutions.
- Proficiency with Python is required, and experience with Golang is a plus.
- Demonstrated technical leadership in guiding teams, owning end-to-end projects, and setting the technical direction to achieve project goals efficiently.
- Experience working with relational databases, data warehouses, and using SQL to explore them.
- Strong familiarity with AWS cloud services, especially in deploying and managing machine learning solutions and scaling them in a cost-effective manner.
- Knowledgeable in Kubernetes, Docker, and CI/CD pipelines for efficient deployment and management of ML models.
- Comfortable with monitoring and observability tools tailored for machine learning models (e.g., Prometheus, Grafana, AWS CloudWatch) and experienced in developing recommender systems or enhancing user experiences through personalized recommendations.
- Solid foundation in data processing and pipeline frameworks (e.g., Apache Spark, Kafka) for handling real-time data streams.
About You:
- You have relentlessly high standards - many people may think your standards are unreasonably high. You are continually raising the bar and driving those around you to deliver great results. You make sure that defects do not get sent down the line and that problems are fixed so they stay fixed.
- You’re not bound by convention - your success—and much of the fun—lies in developing new ways to do things
- You need action - speed matters in business. Many decisions and actions are reversible and do not need extensive study. We value calculated risk-taking.
- You earn trust - you listen attentively, speak candidly, and treat others respectfully.
- You have backbone; disagree, then commit - you can respectfully challenge decisions when you disagree, even when doing so is uncomfortable or exhausting. You have conviction and are tenacious. You do not compromise for the sake of social cohesion. Once a decision is determined, you commit wholly.
- You deliver results - you focus on the key inputs and deliver them with the right quality and in a timely fashion. Despite setbacks, you rise to the occasion and never settle.
What Makes Working at Sezzle Awesome:
At Sezzle, we are more than just brilliant engineers, passionate data enthusiasts, out-of-the-box thinkers, and determined innovators. We believe in surrounding ourselves with only the best and the brightest individuals. Our culture is not defined by a certain set of perks designed to give the illusion of the traditional startup culture, but rather, it is the visible example living in every employee that we hire.
#Li-remote #full-time
Ready to apply?
Apply to SezzleThe salary range for this role is $50,000 - $120,000 per year (Gross in USD)
About Sezzle:
With a mission to financially empower the next generation, Sezzle is revolutionizing the shopping experience beyond payments, blending cutting-edge tech with seamless, interest-free installment plans that make shopping smarter and more accessible. We’re not just transforming payments; we’re redefining how people discover, interact with, and purchase the things they love while driving real impact on merchant sales through increased conversions and higher order values. As we continue to shape the future of fintech and retail, we’re building an innovative, dynamic team passionate about creating more than just a transaction but a truly unique shopping journey. If you’re excited about pushing boundaries in tech and delivering a game-changing experience for consumers and merchants alike, come join us at Sezzle and help create the future of shopping!
About the Role:
We are seeking a talented and motivated Sr. AI engineer who is best in class with a high IQ plus a high EQ. This role presents an exciting opportunity to thrive in a dynamic, fast-paced environment within a rapidly growing team, with abundant prospects for career advancement.
You will be responsible for overseeing the design, development, and deployment of machine learning models that power and enhance our financial platform. In this role, you will drive the creation of scalable machine learning solutions for personalized recommendations in the Sezzle marketplace, fraud detection, and credit risk assessment, utilizing a combination of cloud services, open-source tools, and proprietary algorithms.
Your leadership will be key in blending machine learning development and operations (MLOps) to automate and optimize the full lifecycle of our ML models. You will collaborate with a team of engineers and data scientists to build large-scale, high-quality solutions that address diverse challenges in the shopping and fintech space. You’ll ensure our AI-driven features are robust, efficient, and scalable as we continue to grow.
What You'll Do:
- Design, Build, and Maintain Scalable ML Infrastructure: Lead the design and development of scalable machine learning infrastructure on AWS, utilizing services like AWS Sagemaker for efficient model training and deployment.
- Collaborate with Product Teams: Work closely with product teams to develop MVPs for AI-driven features, ensuring quick iterations and market testing to refine solutions effectively.
- Develop Monitoring & Alerting Frameworks: Create and enhance monitoring and alerting systems for machine learning models to ensure high performance, reliability, and minimal downtime.
- Support Cross-Departmental AI Utilization: Enable various departments within the organization to leverage AI/ML models, including cutting-edge Generative AI solutions, for different use cases.
- Provide Production Support: Offer expertise in debugging and resolving issues related to machine learning models in production, participating in on-call rotations for operational troubleshooting and incident resolution.
- Scale ML Architecture: Design and scale machine learning architecture to support rapid user growth, leveraging deep knowledge of AWS and ML best practices to ensure robustness and efficiency.
- Mentor and Elevate Team Skills: Conduct code reviews, mentor team members, and elevate overall team capabilities through knowledge sharing and collaboration.
- Stay Ahead of the Curve: Stay updated with the latest advancements in machine learning technologies and AWS services, driving the adoption of cutting-edge solutions to maintain a competitive edge.
What We Look For:
- Bachelor's degree in Computer Science, Computer Engineering, Machine Learning, Statistics, Physics, or a relevant technical field, or equivalent practical experience.
- At least 6+ years of experience in machine learning engineering, with demonstrated success in deploying scalable ML models in a production environment.
Preferred Qualifications:
- Deep expertise in one or more of the following areas: machine learning, recommendation systems, pattern recognition, data mining, artificial intelligence, or related technical fields.
- Proven track record of developing machine learning models from inception to business impact, demonstrating the ability to solve complex challenges with innovative solutions.
- Proficiency with Python is required, and experience with Golang is a plus.
- Demonstrated technical leadership in guiding teams, owning end-to-end projects, and setting the technical direction to achieve project goals efficiently.
- Experience working with relational databases, data warehouses, and using SQL to explore them.
- Strong familiarity with AWS cloud services, especially in deploying and managing machine learning solutions and scaling them in a cost-effective manner.
- Knowledgeable in Kubernetes, Docker, and CI/CD pipelines for efficient deployment and management of ML models.
- Comfortable with monitoring and observability tools tailored for machine learning models (e.g., Prometheus, Grafana, AWS CloudWatch) and experienced in developing recommender systems or enhancing user experiences through personalized recommendations.
- Solid foundation in data processing and pipeline frameworks (e.g., Apache Spark, Kafka) for handling real-time data streams.
About You:
- You have relentlessly high standards - many people may think your standards are unreasonably high. You are continually raising the bar and driving those around you to deliver great results. You make sure that defects do not get sent down the line and that problems are fixed so they stay fixed.
- You’re not bound by convention - your success—and much of the fun—lies in developing new ways to do things
- You need action - speed matters in business. Many decisions and actions are reversible and do not need extensive study. We value calculated risk-taking.
- You earn trust - you listen attentively, speak candidly, and treat others respectfully.
- You have backbone; disagree, then commit - you can respectfully challenge decisions when you disagree, even when doing so is uncomfortable or exhausting. You have conviction and are tenacious. You do not compromise for the sake of social cohesion. Once a decision is determined, you commit wholly.
- You deliver results - you focus on the key inputs and deliver them with the right quality and in a timely fashion. Despite setbacks, you rise to the occasion and never settle.
What Makes Working at Sezzle Awesome:
At Sezzle, we are more than just brilliant engineers, passionate data enthusiasts, out-of-the-box thinkers, and determined innovators. We believe in surrounding ourselves with only the best and the brightest individuals. Our culture is not defined by a certain set of perks designed to give the illusion of the traditional startup culture, but rather, it is the visible example living in every employee that we hire.
#Li-remote #full-time
Ready to apply?
Apply to SezzleThe salary range for this role is $50,000 - $120,000 per year (Gross in USD)
About Sezzle:
With a mission to financially empower the next generation, Sezzle is revolutionizing the shopping experience beyond payments, blending cutting-edge tech with seamless, interest-free installment plans that make shopping smarter and more accessible. We’re not just transforming payments; we’re redefining how people discover, interact with, and purchase the things they love while driving real impact on merchant sales through increased conversions and higher order values. As we continue to shape the future of fintech and retail, we’re building an innovative, dynamic team passionate about creating more than just a transaction but a truly unique shopping journey. If you’re excited about pushing boundaries in tech and delivering a game-changing experience for consumers and merchants alike, come join us at Sezzle and help create the future of shopping!
About the Role:
We are seeking a talented and motivated Sr. AI engineer who is best in class with a high IQ plus a high EQ. This role presents an exciting opportunity to thrive in a dynamic, fast-paced environment within a rapidly growing team, with abundant prospects for career advancement.
You will be responsible for overseeing the design, development, and deployment of machine learning models that power and enhance our financial platform. In this role, you will drive the creation of scalable machine learning solutions for personalized recommendations in the Sezzle marketplace, fraud detection, and credit risk assessment, utilizing a combination of cloud services, open-source tools, and proprietary algorithms.
Your leadership will be key in blending machine learning development and operations (MLOps) to automate and optimize the full lifecycle of our ML models. You will collaborate with a team of engineers and data scientists to build large-scale, high-quality solutions that address diverse challenges in the shopping and fintech space. You’ll ensure our AI-driven features are robust, efficient, and scalable as we continue to grow.
What You'll Do:
- Design, Build, and Maintain Scalable ML Infrastructure: Lead the design and development of scalable machine learning infrastructure on AWS, utilizing services like AWS Sagemaker for efficient model training and deployment.
- Collaborate with Product Teams: Work closely with product teams to develop MVPs for AI-driven features, ensuring quick iterations and market testing to refine solutions effectively.
- Develop Monitoring & Alerting Frameworks: Create and enhance monitoring and alerting systems for machine learning models to ensure high performance, reliability, and minimal downtime.
- Support Cross-Departmental AI Utilization: Enable various departments within the organization to leverage AI/ML models, including cutting-edge Generative AI solutions, for different use cases.
- Provide Production Support: Offer expertise in debugging and resolving issues related to machine learning models in production, participating in on-call rotations for operational troubleshooting and incident resolution.
- Scale ML Architecture: Design and scale machine learning architecture to support rapid user growth, leveraging deep knowledge of AWS and ML best practices to ensure robustness and efficiency.
- Mentor and Elevate Team Skills: Conduct code reviews, mentor team members, and elevate overall team capabilities through knowledge sharing and collaboration.
- Stay Ahead of the Curve: Stay updated with the latest advancements in machine learning technologies and AWS services, driving the adoption of cutting-edge solutions to maintain a competitive edge.
What We Look For:
- Bachelor's degree in Computer Science, Computer Engineering, Machine Learning, Statistics, Physics, or a relevant technical field, or equivalent practical experience.
- At least 6+ years of experience in machine learning engineering, with demonstrated success in deploying scalable ML models in a production environment.
Preferred Qualifications:
- Deep expertise in one or more of the following areas: machine learning, recommendation systems, pattern recognition, data mining, artificial intelligence, or related technical fields.
- Proven track record of developing machine learning models from inception to business impact, demonstrating the ability to solve complex challenges with innovative solutions.
- Proficiency with Python is required, and experience with Golang is a plus.
- Demonstrated technical leadership in guiding teams, owning end-to-end projects, and setting the technical direction to achieve project goals efficiently.
- Experience working with relational databases, data warehouses, and using SQL to explore them.
- Strong familiarity with AWS cloud services, especially in deploying and managing machine learning solutions and scaling them in a cost-effective manner.
- Knowledgeable in Kubernetes, Docker, and CI/CD pipelines for efficient deployment and management of ML models.
- Comfortable with monitoring and observability tools tailored for machine learning models (e.g., Prometheus, Grafana, AWS CloudWatch) and experienced in developing recommender systems or enhancing user experiences through personalized recommendations.
- Solid foundation in data processing and pipeline frameworks (e.g., Apache Spark, Kafka) for handling real-time data streams.
About You:
- You have relentlessly high standards - many people may think your standards are unreasonably high. You are continually raising the bar and driving those around you to deliver great results. You make sure that defects do not get sent down the line and that problems are fixed so they stay fixed.
- You’re not bound by convention - your success—and much of the fun—lies in developing new ways to do things
- You need action - speed matters in business. Many decisions and actions are reversible and do not need extensive study. We value calculated risk-taking.
- You earn trust - you listen attentively, speak candidly, and treat others respectfully.
- You have backbone; disagree, then commit - you can respectfully challenge decisions when you disagree, even when doing so is uncomfortable or exhausting. You have conviction and are tenacious. You do not compromise for the sake of social cohesion. Once a decision is determined, you commit wholly.
- You deliver results - you focus on the key inputs and deliver them with the right quality and in a timely fashion. Despite setbacks, you rise to the occasion and never settle.
What Makes Working at Sezzle Awesome:
At Sezzle, we are more than just brilliant engineers, passionate data enthusiasts, out-of-the-box thinkers, and determined innovators. We believe in surrounding ourselves with only the best and the brightest individuals. Our culture is not defined by a certain set of perks designed to give the illusion of the traditional startup culture, but rather, it is the visible example living in every employee that we hire.
#Li-remote #full-time
Ready to apply?
Apply to SezzlePrincipal AI Engineer - Frontier Data
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About Turing
Based in San Francisco, California, Turing is the world’s leading research accelerator for frontier AI labs and a trusted partner for global enterprises looking to deploy advanced AI systems. Turing accelerates frontier research with high-quality data, specialized talent, and training pipelines that advance thinking, reasoning, coding, multimodality, and STEM. For enterprises, Turing builds proprietary intelligence systems that integrate AI into mission-critical workflows, unlock transformative outcomes, and drive lasting competitive advantage.
Recognized by Forbes, The Information, and Fast Company among the world’s top innovators, Turing’s leadership team includes AI technologists from Meta, Google, Microsoft, Apple, Amazon, McKinsey, Bain, Stanford, Caltech, and MIT. Learn more at www.turing.com
The Role
We are looking for an elite engineer who builds like a hacker and communicates like a consultant. You will not just be building models in a notebook; you will be deployed to the front lines to build, architect, and ship end-to-end Agentic AI products directly for our most strategic customers.
This is a high-stakes role. You will face "tricky" customers who have vague requirements and high expectations. Your job is to translate their chaos into technical order, write production-grade code, and deploy autonomous agents that solve their actual business problems.
What You Will Do
- Build & Deploy (60%):
Design and ship full-stack AI applications. You own the pipeline from data ingestion to the LLM inference layer to the frontend interface.
Architect autonomous agentic workflows (using frameworks like LangChain, LangGraph, or custom implementations) that can reason, plan, and execute complex tasks.
Write robust, clean, and highly testable code (Python/Typescript). "It works on my machine" is not acceptable; it must work in the customer's restricted cloud environment.
Handle DevOps and MLOps constraints: Dockerizing agents, managing Kubernetes clusters, and optimizing inference latency.
- Customer Engineering (40%):
Serve as the technical face of the company for our most demanding accounts.
Navigate complex stakeholder environments. You will push back on unrealistic demands, clarify ambiguous requirements, and steer "tricky" customers toward technically feasible solutions without breaking rapport.
Translate technical constraints into business value for non-technical executives.
Generate high-quality data for our customers and ability to review the data generated by other experts. This is one of the most critical aspects of the role.
The "Must-Haves"
- Experience: 8–12 years of total engineering experience. You started as a strong Software Engineer and evolved into an AI specialist.
- Education: B.S./M.S. in Computer Science, Math, or Physics from a top-tier institution (IIT, MIT, Stanford, Harvard, Berkeley, CMU, or similar global top-ranking universities).
- Deep AI Fluency: You aren't just calling APIs. You understand RAG implementation nuances, vector database optimization, fine-tuning (LoRA/PEFT), and the architecture of agentic loops.
- Production Engineering: Experience with end-to-end deployment (AWS/GCP/Azure, CI/CD pipelines, Terraform, Docker).
The "Why You" (Soft Skills)
- Thick Skin & High EQ: You don't get flustered when a customer changes their mind for the third time in a week. You can hold your ground with a CTO and explain "why not" to a CEO.
- Extreme Attention to Detail: You catch the edge cases that others miss. You obsess over error handling, retry logic in agents, and data privacy.
- Grit: You enjoy the "messy" work of integrating legacy enterprise data just as much as prompting the latest model.
What will set you apart
- Public Code: A visible GitHub footprint is very helpful. We want to see your side projects, your contributions to open source, or your experiments with LLMs. Please include your GitHub link in your application.
Tech Stack
- Languages: Python (Expert).
- AI/Data (Expertise in all is not required): PyTorch, LangChain, LlamaIndex, Pinecone/Weaviate, OpenAI/Anthropic APIs, HuggingFace.
- Infra (Expertise in all is not required): Kubernetes, Terraform, AWS/GCP.
Values
- We are client first: We put our clients at the center of everything we do, because their success is the ultimate measure of our value.
- We work at Start-Up Speed: We move fast, stay agile and favor action because momentum is the foundation of perfection
- We are Al forward: We help our clients build the future of Al and implement it in our own roles and workflow to amplify productivity.
Advantages of joining Turing
- Amazing work culture (Super collaborative & supportive work environment; 5 days a week)
- Awesome colleagues (Surround yourself with top talent from Meta, Google, LinkedIn etc. as well as people with deep startup experience)
- Competitive compensation
- Flexible working hours
Don’t meet every single requirement? Studies have shown that women and people of color are less likely to apply to jobs unless they meet every single qualification. Turing is proud to be an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity, sexual orientation, age, marital status, disability, protected veteran status, or any other legally protected characteristics. At Turing we are dedicated to building a diverse, inclusive and authentic workplace and celebrate authenticity, so if you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles.
For applicants from the European Union, please review Turing's GDPR notice here.
Ready to apply?
Apply to TuringInovalon was founded in 1998 on the belief that technology, and data specifically, would empower the transformation of the entire healthcare ecosystem for the better, improving both outcomes and economics. At Inovalon, we believe that when our customers are successful in their missions, healthcare improves. Therefore, we focus on empowering them with data-driven solutions. And the momentum is building.
Together, as ONE Inovalon, we are a united force delivering solutions that address healthcare’s greatest needs. Through our mission-based culture of inclusion and innovation, our organization brings value not just to our customers, but to the millions of patients and members they serve.
About Us:
Inovalon is a leading healthcare technology company dedicated to revolutionizing the healthcare industry through innovative AI and machine learning solutions. Our mission is to leverage cutting-edge technology to improve health outcomes and streamline healthcare processes.
Role overview
As an MLOps Engineer, you will design, build, and operate the infrastructure and tooling that power end-to-end ML workflows on AWS, including SageMaker, Bedrock, and Snowflake Cortex. You will partner closely with data scientists, ML engineers, and platform teams to ensure models are reliable, secure, and scalable in production.
Key responsibilities
- Design, implement, and maintain CI/CD pipelines for ML models and data workflows using AWS-native services and infrastructure-as-code.
- Operationalize models built on SageMaker, Bedrock, and Snowflake Cortex, including feature pipelines, training, batch/real-time inference, and monitoring.
- Build and manage data pipelines and feature stores using services such as AWS Glue, Lambda, Step Functions, and Snowflake.
- Implement observability for ML systems (logging, metrics, tracing, drift/quality monitoring) and establish SLOs/SLAs for production ML services.
- Automate environment provisioning, configuration, and dependency management across dev, test, and production.
- Partner with security and compliance teams to ensure ML workloads meet healthcare, privacy, and regulatory standards (e.g., HIPAA).
- Collaborate with ML engineers and data scientists to productionize notebooks and prototypes into robust, maintainable services.
- Contribute to best practices, standards, and documentation for ML platform and operations across the organization.
Qualifications
- Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or a related field.
- 4+ years of experience in software engineering, data engineering, or ML engineering with at least 2+ years focused on MLOps or ML platform work.
- Strong proficiency with Python and experience integrating ML libraries or frameworks (e.g., scikit-learn, TensorFlow, PyTorch) into production workflows.
- Hands-on expertise with AWS services relevant to MLOps: SageMaker, Bedrock, IAM, CloudWatch, ECR, ECS/EKS or Lambda, S3, Step Functions, and Glue.
- Experience with Snowflake (including Snowflake Cortex), SQL, and building secure, performant data pipelines into and out of Snowflake.
- Proficiency with CI/CD tools (e.g., GitHub Actions, GitLab CI, CodePipeline) and infrastructure-as-code (e.g., Terraform, CloudFormation, CDK).
- Familiarity with containerization and orchestration (Docker, Kubernetes) and event streaming tools (e.g., Kafka) is a plus.
- Knowledge of software engineering best practices, including testing, code reviews, version control, and design for reliability and scalability.
- Experience in regulated domains or with healthcare data standards and regulations is a plus (e.g., HIPAA, FHIR, HL7).
Soft skills and benefits
- Excellent problem-solving and analytical skills with a focus on reliability and automation.
- Strong communication and collaboration abilities, including working cross-functionally with engineering, data science, and product teams.
- Ability to work independently in a fast-paced environment
- Competitive salary and benefits package.
- Opportunity to work on impactful ML platforms that improve healthcare outcomes.
- Collaborative, innovative environment with professional development and growth opportunities.
This position is not eligible for immigration sponsorship (e.g. H-1B, TN, or E-3). Applicants must be authorized to work in the United States as a condition of employment. (This is only applicable for US-based positions)
If you don’t meet every qualification listed but are excited about our mission and the work described, we encourage you to apply. Inovalon is most interested in finding the best candidate for the job, and you may be just the right person for this or other roles.
By embracing inclusion, we enhance our work environment and drive business success. Inovalon strives to provide equal opportunities to the communities where we operate and to our clients and everyone whom we serve. We endeavor to create a culture of inclusion in which our associates feel empowered to bring their full, authentic selves to work and pursue their professional goals in an equitable setting. We understand that by fostering this type of culture, and welcoming different perspectives, we generate innovation and growth.
Inovalon is proud to be an equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirement.
To review the legal requirements, including all labor law posters, please visit this link
To review the California Consumer Privacy Statement: Disclosures for California Residents, please visit this link
Ready to apply?
Apply to Inovalon
At Anaplan, we are a team of innovators focused on optimizing business decision-making through our leading AI-infused scenario planning and analysis platform so our customers can outpace their competition and the market.
What unites Anaplanners across teams and geographies is our collective commitment to our customers’ success and to our Winning Culture.
Our customers rank among the who’s who in the Fortune 50. Coca-Cola, LinkedIn, Adobe, LVMH and Bayer are just a few of the 2,400+ global companies who rely on our best-in-class platform.
Our Winning Culture is the engine that drives our teams of innovators. We champion diversity of thought and ideas, we behave like leaders regardless of title, we are committed to achieving ambitious goals, and we love celebrating our wins – big and small.
Supported by operating principles of being strategy-led, values-based and disciplined in execution, you’ll be inspired, connected, developed and rewarded here. Everything that makes you unique is welcome; join us and let’s build what’s next - together!
About the Role
Anaplan is looking for a skilled Python Machine Learning Developer to join our AI engineering organization. This is a crucial, hands-on developer role focused on building the robust backend systems that power our machine learning features. You are not just a developer; you are a software engineer who specializes in bringing ML models to life in a production environment. You will be responsible for designing, building, and deploying the APIs, data pipelines, and backend services necessary to integrate sophisticated machine learning capabilities into the Anaplan platform.
Key Responsibilities
- Design, build, and maintain scalable and reliable machine learning services and APIs using Python.
- Develop and productionize ML models, taking them from prototype to scalable, live systems.
- Construct and manage the data pipelines required for model training, validation, and inference.
- Build and interact with databases (both SQL and NoSQL) to store and retrieve data for ML applications.
- Write clean, high-quality, and well-tested code, adhering to software engineering best practices.
- Collaborate with data scientists, AI architects, and other engineers to integrate ML models into our products.
- Optimize applications for speed, scalability, and reliability.
- Contribute to our MLOps infrastructure to streamline the deployment and monitoring of machine learning models.
Required Qualifications
- Expert (6+ years) Python Programming: Strong, hands-on proficiency in Python for software development.
- Backend & API Development: Proven experience building and deploying backend services and RESTful APIs using frameworks like Flask, FastAPI, or Django.
- Database Proficiency: Solid experience with both SQL (e.g., PostgreSQL) and NoSQL (e.g., MongoDB, Redis) databases, including data modeling and query optimization.
- Machine Learning Libraries: Deep, practical knowledge of the core Python ML ecosystem:
- Data manipulation and analysis: Pandas, NumPy.
- Core ML frameworks: scikit-learn.
- Deep learning frameworks: Experience with TensorFlow or PyTorch.
- Strong understanding of software engineering principles, including data structures, algorithms, and design patterns.
- Experience with version control (Git) and CI/CD practices.
- Excellent problem-solving skills and the ability to write efficient, production-ready code.
Preferred Qualifications
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
- Experience with cloud platforms (AWS, Azure, or GCP) and their ML services.
- Familiarity with containerization technologies like Docker and orchestration with Kubernetes.
- Experience with MLOps tools and principles (e.g., MLflow, Kubeflow).
- Knowledge of large-scale data processing frameworks like Spark or Dask.
What Makes This Role Exciting
This role places you at the critical intersection of software engineering and machine learning. You are a builder, responsible for creating the tangible systems that make our AI intelligent. You will tackle complex engineering challenges, from API design to database performance, all within the context of delivering cutting-edge machine learning features. At Anaplan, you will see your code run at scale, directly impacting a product used by leading global enterprises and solving real-world business problems.
Our Commitment to Diversity, Equity, Inclusion and Belonging (DEIB)
We believe attracting and retaining the best talent and fostering an inclusive culture strengthens our business. DEIB improves our workforce, enhances trust with our partners and customers, and drives business success. Build your career in a place where diversity, equity, inclusion and belonging aren’t just words on paper – this is what drives our innovation, it’s how we connect, and it contributes to what makes us a market leader. We believe in a hiring and working environment where all people are respected and valued, regardless of gender identity or expression, sexual orientation, religion, ethnicity, age, neurodiversity, disability status, citizenship, or any other aspect which makes people unique. We hire you for who you are, and we want you to bring your authentic self to work every day!
We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, perform essential job functions, and receive equitable benefits and all privileges of employment. Please contact us to request accommodation.
Fraud Recruitment Disclaimer
It has come to our attention that fraudulent and fictitious job opportunities are being circulated on the Internet. Prospective candidates are being contacted by certain individuals, mainly through telephone calls, emails and correspondence, claiming they are representatives of Anaplan. The main purpose of these correspondences and announcements is to obtain privileged information from individuals.
Anaplan does not:
- Extend offers to candidates without an extensive interview process with a member of our recruitment team and a hiring manager via video or in person.
- Send job offers via email. All offers are first extended verbally by a member of our internal recruitment team whenever possible and then followed up via written communication.
All emails from Anaplan would come from an @anaplan.com email address. Should you have any doubts about the authenticity of an email, letter or telephone communication purportedly from, for, or on behalf of Anaplan, please send an email to people@anaplan.com before taking any further action in relation to the correspondence.
Ready to apply?
Apply to AnaplanAt Anaplan, we are a team of innovators focused on optimizing business decision-making through our leading AI-infused scenario planning and analysis platform so our customers can outpace their competition and the market.
What unites Anaplanners across teams and geographies is our collective commitment to our customers’ success and to our Winning Culture.
Our customers rank among the who’s who in the Fortune 50. Coca-Cola, LinkedIn, Adobe, LVMH and Bayer are just a few of the 2,400+ global companies who rely on our best-in-class platform.
Our Winning Culture is the engine that drives our teams of innovators. We champion diversity of thought and ideas, we behave like leaders regardless of title, we are committed to achieving ambitious goals, and we love celebrating our wins – big and small.
Supported by operating principles of being strategy-led, values-based and disciplined in execution, you’ll be inspired, connected, developed and rewarded here. Everything that makes you unique is welcome; join us and let’s build what’s next - together!
About the Role
Anaplan is on a mission to revolutionize business planning by connecting organizations and people to make better, faster decisions. We are seeking a visionary Senior Manager for AI Engineering to lead our talented team in building the next generation of intelligent planning solutions. This is a critical leadership role where you will drive the technical strategy and execution for AI/ML initiatives, directly impacting Anaplan’s product and our customers' success. You will be at the forefront of integrating cutting-edge AI, from time series forecasting to generative and agentic AI, into our market-leading platform.
Key Responsibilities
- Lead, mentor, and grow a high-performing team of AI/ML engineers, fostering a culture of innovation, collaboration, and excellence.
- Define and execute the roadmap for AI/ML projects, ensuring alignment with business objectives and product strategy.
- Architect and oversee the development of scalable, robust, and production-grade AI systems on cloud platforms (AWS, Azure, GCP).
- Drive best practices for the full machine learning lifecycle, including MLOps, CI/CD for ML, model monitoring, and governance.
- Collaborate closely with product managers, data scientists, and other engineering leaders to translate business requirements into technical solutions.
- Stay at the forefront of advancements in AI/ML, including Large Language Models (LLMs) and agentic AI, to identify and implement new opportunities.
- Manage project timelines, resources, and stakeholder communication to ensure the timely delivery of high-quality AI solutions.
Required Qualifications
- Proven experience leading AI/ML teams in a SaaS or enterprise software environment.
- Deep expertise in time series forecasting and machine learning.
- Experience architecting and deploying scalable, production-grade AI systems on cloud platforms (AWS, Azure, GCP).
- Solid understanding of MLOps, CI/CD for ML, and cloud-native architectures.
- Deep knowledge of LLM APIs, prompt engineering, and conversational AI patterns.
- Experience with agentic frameworks and autonomous agent architectures.
- Proficiency in Python and modern software development practices (testing, code review, CI/CD).
- Proven track record of delivering complex technical projects on time with high quality.
- Excellent communication, collaboration, and stakeholder management skills.
- Track record of delivering impactful AI solutions in a fast-paced, agile environment.
Preferred Qualifications
- Master’s or Ph.D. in Computer Science, AI, Machine Learning, or a related field.
- Experience with large-scale data processing frameworks like Spark.
- Familiarity with the challenges of applying AI in enterprise planning or financial domains.
- A portfolio of published research or contributions to open-source AI projects.
- Experience requrired - 15+ Yrears
What Makes This Role Exciting
You will be a key leader in Anaplan’s AI journey, with the autonomy to shape our technical direction and build a world-class engineering team. This is a unique opportunity to solve complex, real-world problems and deliver intelligent solutions that empower major global enterprises to make more informed decisions. You will work with a passionate team on the cutting edge of AI, making a tangible impact on our product and the industry.
Our Commitment to Diversity, Equity, Inclusion and Belonging (DEIB)
We believe attracting and retaining the best talent and fostering an inclusive culture strengthens our business. DEIB improves our workforce, enhances trust with our partners and customers, and drives business success. Build your career in a place where diversity, equity, inclusion and belonging aren’t just words on paper – this is what drives our innovation, it’s how we connect, and it contributes to what makes us a market leader. We believe in a hiring and working environment where all people are respected and valued, regardless of gender identity or expression, sexual orientation, religion, ethnicity, age, neurodiversity, disability status, citizenship, or any other aspect which makes people unique. We hire you for who you are, and we want you to bring your authentic self to work every day!
We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, perform essential job functions, and receive equitable benefits and all privileges of employment. Please contact us to request accommodation.
Fraud Recruitment Disclaimer
It has come to our attention that fraudulent and fictitious job opportunities are being circulated on the Internet. Prospective candidates are being contacted by certain individuals, mainly through telephone calls, emails and correspondence, claiming they are representatives of Anaplan. The main purpose of these correspondences and announcements is to obtain privileged information from individuals.
Anaplan does not:
- Extend offers to candidates without an extensive interview process with a member of our recruitment team and a hiring manager via video or in person.
- Send job offers via email. All offers are first extended verbally by a member of our internal recruitment team whenever possible and then followed up via written communication.
All emails from Anaplan would come from an @anaplan.com email address. Should you have any doubts about the authenticity of an email, letter or telephone communication purportedly from, for, or on behalf of Anaplan, please send an email to people@anaplan.com before taking any further action in relation to the correspondence.
Ready to apply?
Apply to AnaplanAt Anaplan, we are a team of innovators focused on optimizing business decision-making through our leading AI-infused scenario planning and analysis platform so our customers can outpace their competition and the market.
What unites Anaplanners across teams and geographies is our collective commitment to our customers’ success and to our Winning Culture.
Our customers rank among the who’s who in the Fortune 50. Coca-Cola, LinkedIn, Adobe, LVMH and Bayer are just a few of the 2,400+ global companies who rely on our best-in-class platform.
Our Winning Culture is the engine that drives our teams of innovators. We champion diversity of thought and ideas, we behave like leaders regardless of title, we are committed to achieving ambitious goals, and we love celebrating our wins – big and small.
Supported by operating principles of being strategy-led, values-based and disciplined in execution, you’ll be inspired, connected, developed and rewarded here. Everything that makes you unique is welcome; join us and let’s build what’s next - together!
About the Role
Anaplan is looking for a skilled Python Machine Learning Developer to join our AI engineering organization. This is a crucial, hands-on developer role focused on building the robust backend systems that power our machine learning features. You are not just a developer; you are a software engineer who specializes in bringing ML models to life in a production environment. You will be responsible for designing, building, and deploying the APIs, data pipelines, and backend services necessary to integrate sophisticated machine learning capabilities into the Anaplan platform.
Key Responsibilities
- Design, build, and maintain scalable and reliable machine learning services and APIs using Python.
- Develop and productionize ML models, taking them from prototype to scalable, live systems.
- Construct and manage the data pipelines required for model training, validation, and inference.
- Build and interact with databases (both SQL and NoSQL) to store and retrieve data for ML applications.
- Write clean, high-quality, and well-tested code, adhering to software engineering best practices.
- Collaborate with data scientists, AI architects, and other engineers to integrate ML models into our products.
- Optimize applications for speed, scalability, and reliability.
- Contribute to our MLOps infrastructure to streamline the deployment and monitoring of machine learning models.
Required Qualifications
- Expert (10+ years) Python Programming: Strong, hands-on proficiency in Python for software development.
- Backend & API Development: Proven experience building and deploying backend services and RESTful APIs using frameworks like Flask, FastAPI, or Django.
- Database Proficiency: Solid experience with both SQL (e.g., PostgreSQL) and NoSQL (e.g., MongoDB, Redis) databases, including data modeling and query optimization.
- Machine Learning Libraries: Deep, practical knowledge of the core Python ML ecosystem:
- Data manipulation and analysis: Pandas, NumPy.
- Core ML frameworks: scikit-learn.
- Deep learning frameworks: Experience with TensorFlow or PyTorch.
- Strong understanding of software engineering principles, including data structures, algorithms, and design patterns.
- Experience with version control (Git) and CI/CD practices.
- Excellent problem-solving skills and the ability to write efficient, production-ready code.
Preferred Qualifications
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
- Experience with cloud platforms (AWS, Azure, or GCP) and their ML services.
- Familiarity with containerization technologies like Docker and orchestration with Kubernetes.
- Experience with MLOps tools and principles (e.g., MLflow, Kubeflow).
- Knowledge of large-scale data processing frameworks like Spark or Dask.
What Makes This Role Exciting
This role places you at the critical intersection of software engineering and machine learning. You are a builder, responsible for creating the tangible systems that make our AI intelligent. You will tackle complex engineering challenges, from API design to database performance, all within the context of delivering cutting-edge machine learning features. At Anaplan, you will see your code run at scale, directly impacting a product used by leading global enterprises and solving real-world business problems.
Our Commitment to Diversity, Equity, Inclusion and Belonging (DEIB)
We believe attracting and retaining the best talent and fostering an inclusive culture strengthens our business. DEIB improves our workforce, enhances trust with our partners and customers, and drives business success. Build your career in a place where diversity, equity, inclusion and belonging aren’t just words on paper – this is what drives our innovation, it’s how we connect, and it contributes to what makes us a market leader. We believe in a hiring and working environment where all people are respected and valued, regardless of gender identity or expression, sexual orientation, religion, ethnicity, age, neurodiversity, disability status, citizenship, or any other aspect which makes people unique. We hire you for who you are, and we want you to bring your authentic self to work every day!
We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, perform essential job functions, and receive equitable benefits and all privileges of employment. Please contact us to request accommodation.
Fraud Recruitment Disclaimer
It has come to our attention that fraudulent and fictitious job opportunities are being circulated on the Internet. Prospective candidates are being contacted by certain individuals, mainly through telephone calls, emails and correspondence, claiming they are representatives of Anaplan. The main purpose of these correspondences and announcements is to obtain privileged information from individuals.
Anaplan does not:
- Extend offers to candidates without an extensive interview process with a member of our recruitment team and a hiring manager via video or in person.
- Send job offers via email. All offers are first extended verbally by a member of our internal recruitment team whenever possible and then followed up via written communication.
All emails from Anaplan would come from an @anaplan.com email address. Should you have any doubts about the authenticity of an email, letter or telephone communication purportedly from, for, or on behalf of Anaplan, please send an email to people@anaplan.com before taking any further action in relation to the correspondence.
Ready to apply?
Apply to AnaplanAt Anaplan, we are a team of innovators focused on optimizing business decision-making through our leading AI-infused scenario planning and analysis platform so our customers can outpace their competition and the market.
What unites Anaplanners across teams and geographies is our collective commitment to our customers’ success and to our Winning Culture.
Our customers rank among the who’s who in the Fortune 50. Coca-Cola, LinkedIn, Adobe, LVMH and Bayer are just a few of the 2,400+ global companies who rely on our best-in-class platform.
Our Winning Culture is the engine that drives our teams of innovators. We champion diversity of thought and ideas, we behave like leaders regardless of title, we are committed to achieving ambitious goals, and we love celebrating our wins – big and small.
Supported by operating principles of being strategy-led, values-based and disciplined in execution, you’ll be inspired, connected, developed and rewarded here. Everything that makes you unique is welcome; join us and let’s build what’s next - together!
About the Role
Anaplan is on a mission to revolutionize business planning by connecting organizations and people to make better, faster decisions. We are seeking a visionary Senior Manager for AI Engineering to lead our talented team in building the next generation of intelligent planning solutions. This is a critical leadership role where you will drive the technical strategy and execution for AI/ML initiatives, directly impacting Anaplan’s product and our customers' success. You will be at the forefront of integrating cutting-edge AI, from time series forecasting to generative and agentic AI, into our market-leading platform.
Key Responsibilities
- Lead, mentor, and grow a high-performing team of AI/ML engineers, fostering a culture of innovation, collaboration, and excellence.
- Define and execute the roadmap for AI/ML projects, ensuring alignment with business objectives and product strategy.
- Architect and oversee the development of scalable, robust, and production-grade AI systems on cloud platforms (AWS, Azure, GCP).
- Drive best practices for the full machine learning lifecycle, including MLOps, CI/CD for ML, model monitoring, and governance.
- Collaborate closely with product managers, data scientists, and other engineering leaders to translate business requirements into technical solutions.
- Stay at the forefront of advancements in AI/ML, including Large Language Models (LLMs) and agentic AI, to identify and implement new opportunities.
- Manage project timelines, resources, and stakeholder communication to ensure the timely delivery of high-quality AI solutions.
Required Qualifications
- Proven experience leading AI/ML teams in a SaaS or enterprise software environment.
- Deep expertise in time series forecasting and machine learning.
- Experience architecting and deploying scalable, production-grade AI systems on cloud platforms (AWS, Azure, GCP).
- Solid understanding of MLOps, CI/CD for ML, and cloud-native architectures.
- Deep knowledge of LLM APIs, prompt engineering, and conversational AI patterns.
- Experience with agentic frameworks and autonomous agent architectures.
- Proficiency in Python and modern software development practices (testing, code review, CI/CD).
- Proven track record of delivering complex technical projects on time with high quality.
- Excellent communication, collaboration, and stakeholder management skills.
- Track record of delivering impactful AI solutions in a fast-paced, agile environment.
Preferred Qualifications
- Master’s or Ph.D. in Computer Science, AI, Machine Learning, or a related field.
- Experience with large-scale data processing frameworks like Spark.
- Familiarity with the challenges of applying AI in enterprise planning or financial domains.
- A portfolio of published research or contributions to open-source AI projects.
- Experience - 15+ years
What Makes This Role Exciting
You will be a key leader in Anaplan’s AI journey, with the autonomy to shape our technical direction and build a world-class engineering team. This is a unique opportunity to solve complex, real-world problems and deliver intelligent solutions that empower major global enterprises to make more informed decisions. You will work with a passionate team on the cutting edge of AI, making a tangible impact on our product and the industry.
Our Commitment to Diversity, Equity, Inclusion and Belonging (DEIB)
We believe attracting and retaining the best talent and fostering an inclusive culture strengthens our business. DEIB improves our workforce, enhances trust with our partners and customers, and drives business success. Build your career in a place where diversity, equity, inclusion and belonging aren’t just words on paper – this is what drives our innovation, it’s how we connect, and it contributes to what makes us a market leader. We believe in a hiring and working environment where all people are respected and valued, regardless of gender identity or expression, sexual orientation, religion, ethnicity, age, neurodiversity, disability status, citizenship, or any other aspect which makes people unique. We hire you for who you are, and we want you to bring your authentic self to work every day!
We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, perform essential job functions, and receive equitable benefits and all privileges of employment. Please contact us to request accommodation.
Fraud Recruitment Disclaimer
It has come to our attention that fraudulent and fictitious job opportunities are being circulated on the Internet. Prospective candidates are being contacted by certain individuals, mainly through telephone calls, emails and correspondence, claiming they are representatives of Anaplan. The main purpose of these correspondences and announcements is to obtain privileged information from individuals.
Anaplan does not:
- Extend offers to candidates without an extensive interview process with a member of our recruitment team and a hiring manager via video or in person.
- Send job offers via email. All offers are first extended verbally by a member of our internal recruitment team whenever possible and then followed up via written communication.
All emails from Anaplan would come from an @anaplan.com email address. Should you have any doubts about the authenticity of an email, letter or telephone communication purportedly from, for, or on behalf of Anaplan, please send an email to people@anaplan.com before taking any further action in relation to the correspondence.
Ready to apply?
Apply to AnaplanAt Anaplan, we are a team of innovators focused on optimizing business decision-making through our leading AI-infused scenario planning and analysis platform so our customers can outpace their competition and the market.
What unites Anaplanners across teams and geographies is our collective commitment to our customers’ success and to our Winning Culture.
Our customers rank among the who’s who in the Fortune 50. Coca-Cola, LinkedIn, Adobe, LVMH and Bayer are just a few of the 2,400+ global companies who rely on our best-in-class platform.
Our Winning Culture is the engine that drives our teams of innovators. We champion diversity of thought and ideas, we behave like leaders regardless of title, we are committed to achieving ambitious goals, and we love celebrating our wins – big and small.
Supported by operating principles of being strategy-led, values-based and disciplined in execution, you’ll be inspired, connected, developed and rewarded here. Everything that makes you unique is welcome; join us and let’s build what’s next - together!
About the Role
Anaplan is looking for a skilled Python Machine Learning Developer to join our AI engineering organization. This is a crucial, hands-on developer role focused on building the robust backend systems that power our machine learning features. You are not just a developer; you are a software engineer who specializes in bringing ML models to life in a production environment. You will be responsible for designing, building, and deploying the APIs, data pipelines, and backend services necessary to integrate sophisticated machine learning capabilities into the Anaplan platform.
Key Responsibilities
- Design, build, and maintain scalable and reliable machine learning services and APIs using Python.
- Develop and productionize ML models, taking them from prototype to scalable, live systems.
- Construct and manage the data pipelines required for model training, validation, and inference.
- Build and interact with databases (both SQL and NoSQL) to store and retrieve data for ML applications.
- Write clean, high-quality, and well-tested code, adhering to software engineering best practices.
- Collaborate with data scientists, AI architects, and other engineers to integrate ML models into our products.
- Optimize applications for speed, scalability, and reliability.
- Contribute to our MLOps infrastructure to streamline the deployment and monitoring of machine learning models.
Required Qualifications
- Expert (6+ years) Python Programming: Strong, hands-on proficiency in Python for software development.
- Backend & API Development: Proven experience building and deploying backend services and RESTful APIs using frameworks like Flask, FastAPI, or Django.
- Database Proficiency: Solid experience with both SQL (e.g., PostgreSQL) and NoSQL (e.g., MongoDB, Redis) databases, including data modeling and query optimization.
- Machine Learning Libraries: Deep, practical knowledge of the core Python ML ecosystem:
- Data manipulation and analysis: Pandas, NumPy.
- Core ML frameworks: scikit-learn.
- Deep learning frameworks: Experience with TensorFlow or PyTorch.
- Strong understanding of software engineering principles, including data structures, algorithms, and design patterns.
- Experience with version control (Git) and CI/CD practices.
- Excellent problem-solving skills and the ability to write efficient, production-ready code.
Preferred Qualifications
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
- Experience with cloud platforms (AWS, Azure, or GCP) and their ML services.
- Familiarity with containerization technologies like Docker and orchestration with Kubernetes.
- Experience with MLOps tools and principles (e.g., MLflow, Kubeflow).
- Knowledge of large-scale data processing frameworks like Spark or Dask.
What Makes This Role Exciting
This role places you at the critical intersection of software engineering and machine learning. You are a builder, responsible for creating the tangible systems that make our AI intelligent. You will tackle complex engineering challenges, from API design to database performance, all within the context of delivering cutting-edge machine learning features. At Anaplan, you will see your code run at scale, directly impacting a product used by leading global enterprises and solving real-world business problems.
Our Commitment to Diversity, Equity, Inclusion and Belonging (DEIB)
We believe attracting and retaining the best talent and fostering an inclusive culture strengthens our business. DEIB improves our workforce, enhances trust with our partners and customers, and drives business success. Build your career in a place where diversity, equity, inclusion and belonging aren’t just words on paper – this is what drives our innovation, it’s how we connect, and it contributes to what makes us a market leader. We believe in a hiring and working environment where all people are respected and valued, regardless of gender identity or expression, sexual orientation, religion, ethnicity, age, neurodiversity, disability status, citizenship, or any other aspect which makes people unique. We hire you for who you are, and we want you to bring your authentic self to work every day!
We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, perform essential job functions, and receive equitable benefits and all privileges of employment. Please contact us to request accommodation.
Fraud Recruitment Disclaimer
It has come to our attention that fraudulent and fictitious job opportunities are being circulated on the Internet. Prospective candidates are being contacted by certain individuals, mainly through telephone calls, emails and correspondence, claiming they are representatives of Anaplan. The main purpose of these correspondences and announcements is to obtain privileged information from individuals.
Anaplan does not:
- Extend offers to candidates without an extensive interview process with a member of our recruitment team and a hiring manager via video or in person.
- Send job offers via email. All offers are first extended verbally by a member of our internal recruitment team whenever possible and then followed up via written communication.
All emails from Anaplan would come from an @anaplan.com email address. Should you have any doubts about the authenticity of an email, letter or telephone communication purportedly from, for, or on behalf of Anaplan, please send an email to people@anaplan.com before taking any further action in relation to the correspondence.
Ready to apply?
Apply to Anaplan