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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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Head of Machine Learning
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At Prodigal, we are building AI Agents for loan servicing and collections. Founded in 2018 by IITB alumni, our journey began with one bold mission: to eradicate the inefficiencies and confusion that have plagued the lending and collections industry for decades. We are backed by Y Combinator, Accel and Menlo Ventures.
Today, we stand at the forefront of a seismic shift in the industry, building Agentic AI applications for consumer finance. Powered by our cutting-edge platform, Prodigal’s Intelligence Engine (PIE), we’re creating the next-generation agentic workforce - one that empowers companies to achieve unprecedented levels of operational excellence and intelligence.
With over half a billion consumer finance interactions processed and a growing impact on more than 100 leading companies across North America, we’ve established ourselves as the go-to partner for organizations that demand more from their AI solutions. Our unparalleled experience, coupled with our trusted customer relationships, uniquely positions us to build Agentic AI applications that will revolutionize the future of consumer finance.
At Prodigal, we are driven by a singular, unrelenting purpose: to transform how consumer finance companies engage with their customers and, in turn, drive successful outcomes for all.
We're seeking a Head of Machine Learning to own and scale the ML function at Prodigal. This is the senior-most ML role in the company — partnering directly with the CTO as a peer technical leader, defining the multi-year ML vision, building and leading a world-class team, and translating cutting-edge research into production systems that move the needle for over 100 customers and millions of consumers. You'll set the bar for technical excellence, hire and develop the next generation of ML leaders, and shape what consumer finance intelligence looks like over the next decade. If you've operated at this level before — or are ready to step into it at a company where ML is the engine of the product — we want to talk.
Responsibilities:
- Own the ML function end-to-end — vision, roadmap, team, delivery, and measurable business impact across classical ML, NLP, GenAI, and Agentic AI
- Partner with the CTO as the senior ML leader to set company-wide technical direction and shape the long-term roadmap for Prodigal's Intelligence Engine
- Build and lead a high-performing ML organization — hire, mentor, and develop ML engineers, applied scientists, and tech leads across multiple pods
- Translate research into product — drive the application of LLMs, Agentic AI, the modern NLP stack, recommendation systems, and classical ML into production systems serving 100+ customers
- Set technical standards for model development, deployment, monitoring, evaluation, and experimentation that scale across the org
- Architect data and ML infrastructure in partnership with the platform and engineering teams to support large-scale training and reliable, low-latency inference
- Communicate strategy and outcomes clearly to the founders, board, customers, and broader engineering organization
- Represent Prodigal externally — at conferences, in research collaborations, and as a senior voice in the consumer finance AI community
- Stay at the frontier of ML and GenAI research, identifying where new techniques unlock product and business advantage
- Collaborate cross-functionally with product, engineering, GTM, and customer success leaders to ensure ML investment ties directly to revenue, retention, and customer outcomes
Requirements:
- 10+ years of experience in machine learning and software development at a tech or product company, with 4+ years leading ML teams (managing engineers and/or tech leads)
- Proven track record of shipping ML products in production at scale with measurable business impact
- Deep technical fluency across classical ML, deep learning, and the modern NLP/LLM stack — you can still go deep in design reviews, not just review at the surface
- Strong coding skills in Python. Hands-on with PyTorch, scikit-learn, Pandas, and Spark
- Demonstrated success hiring, mentoring, and growing ML talent — including team leads and senior engineers
- Strong executive communication and the ability to set technical direction with founders, peers, and the board
- A bias for outcomes — you connect model work to revenue, engagement, and operational metrics
Preferred Qualifications:
- Experience as a founding ML hire, ML lead, or applied science leader at a high-growth AI/ML product company
- Background in voice AI, conversational AI, speech, NLP on unstructured text, or fintech/lending domains
- Experience with cloud services (AWS), Databricks, and building scalable, distributed systems
- Track record of running A/B testing and experimentation programs at scale
- Patents, publications, or open-source contributions; strong institutional pedigree (IIT, BITS, NIT, IISc)
- Experience scaling an ML org through a hypergrowth phase
Job Benefits
- GenAI at the core – Lead the ML function at a company where AI isn't a feature, it's the product. Shape groundbreaking work that redefines consumer finance intelligence.
- World-class team - You'll get the chance to learn from (and teach) some of the brightest and most skilled people you'll ever meet. Our team members have been part of BCG, Deloitte, EY, Blackstone, Meta, Amazon and are IIT, IIM, BITS alumnus.
- Continuous education - As relentless seekers of knowledge, we sponsor and support any training materials, books, courses, and exam fees for upskilling yourself in areas related to your role - but that's not where it ends. If you make a good case for some extra learning, we're delighted to foot the tab.
- Food at the office – Meals are on us. We won't let your stomach grumble while you hustle.
- Health insurance - Health always comes first. The health of your family is as important to us as it is to you. We offer insurance coverage for both you and your family.
- Flexible schedule - We're not a "clock in, clock out" company. Morning person? Start work while the world's still sleeping. Night owl? Ramp things up while others are winding down. You're fully trusted to create the right conditions for your own personal peak productivity. We only ask that you be available to your teammates for seamless collaboration.
- Generous leave policy - Take all the time you need to recharge your batteries - no cap on vacation here. Because a rested, relaxed, and refreshed mind is a happy and effective mind.
- Recreation & team activities – We regularly indulge in friendly football, table tennis, cooking sessions, and challenge each other to do those extra push-ups or chug that 4th drink (of course, that's Nimbu Pani).
Meet Sangram (Cofounder and CTO) and hear his vision for Prodigal: https://www.youtube.com/embed/FTWlN9fwiIA?feature=shared
From day 1, Prodigal has been defined by talented, humble, and hungry leaders and we want this mindset and culture to continue to blossom from top to bottom in the company. If you have an entrepreneurial spirit and want to work in a fast-paced, intellectually-stimulating environment where you will be pushed to grow, then please reach out because we are looking to build a transformational company that reinvents one of the biggest industries in the US.
To learn more about us - please visit the following:
Our Story - https://www.prodigaltech.com/our-story
What shapes our thinking - https://link.prodigaltech.com/our-thesis
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Sr AI/ML Engineer
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As a Senior AI/ML Engineer in our AdTech team, you will be a hands-on individual contributor building and deploying machine learning models and AI-driven features for our advertising platform. You will partner with engineering, product, and data science to deliver production-grade ML for campaign optimization, user personalization, and creative intelligence—operating at large scale and low latency across billions of ad events per day. You will contribute to modern ML/LLM capabilities and agentic workflows that automate and enhance campaign operations, with a strong focus on reliability, performance, and measurable business impact.
Key Responsibilities
- Machine Learning Delivery: Design, implement, and ship scalable ML solutions for core AdTech use cases (targeting, ranking, pacing, measurement). Own features end-to-end from experimentation to production rollout.
- ML System Design: Build and evolve the ML lifecycle—data preparation, training, evaluation, and real-time inference—ensuring models integrate cleanly with ad serving systems and meet low-latency, high-throughput requirements.
- Technical Contribution: Contribute to the AI/ML technical roadmap by evaluating tools and techniques (including deep learning, LLMs, and retrieval/feature systems). Make pragmatic trade-offs with an eye toward maintainability and operational excellence.
- AI & Agentic Applications: Develop and integrate LLM-powered features and agentic workflows that assist with campaign workflows such as audience insights, bid/budget recommendations, and creative generation—within well-defined guardrails.
- Cross-Functional Collaboration: Work closely with engineering, product, and data science partners to translate marketing objectives into ML-driven solutions, define success metrics, and deliver iterative improvements.
- Performance & Reliability: Operate ML services in a high-concurrency, latency-sensitive environment. Optimize inference paths, implement monitoring/alerting, manage model drift, and ensure safe deployment practices (A/B testing, canaries, rollbacks).
- Mentorship & Best Practices: Mentor and support other engineers through code/model reviews and knowledge sharing. Champion engineering rigor in testing, observability, documentation, and reproducible ML workflows.
Required Qualifications
- 5+ years of experience in software engineering and/or applied machine learning, with a track record of shipping ML systems to production.
- Experience designing and building high-throughput, low-latency services or data pipelines for large-scale applications.
- Working knowledge of the programmatic advertising ecosystem (DSP/SSP/RTB) is a plus; strong adjacent experience (recommendation, ranking, marketplaces) is also valued.
- Proficiency in at least one of Java, Go, or Python for backend services and ML tooling.
- Hands-on experience with ML frameworks (PyTorch or TensorFlow) and common modeling approaches (classification, ranking, embeddings, deep learning).
- Experience with big data and streaming frameworks (e.g., Spark, Kafka) for processing and analyzing large datasets.
- Experience deploying ML to cloud environments (preferably AWS) and operating services at scale.
- Familiarity with data stores (SQL/NoSQL) such as PostgreSQL/MySQL, Cassandra/DynamoDB, Redis, etc.
- Familiarity with containerization/orchestration (Docker, Kubernetes) and CI/CD practices.
- Strong communication skills and ability to collaborate across disciplines; comfort explaining technical concepts to both technical and non-technical stakeholders.
Preferred Qualifications
- Experience with Large Language Models (LLMs) and generative AI applied to advertising (e.g., ad copy generation, creative optimization, or personalized messaging).
- Experience designing and implementing agentic workflows that support autonomous or semi-autonomous decision-making with strong safety/observability guardrails.
- Experience with model serving and optimization for real-time inference (latency-critical environments).
- Familiarity with modern data lake and table formats (e.g., Apache Iceberg, Apache Hudi) for managing large-scale analytical datasets.
- Knowledge of microservices architecture and event-driven design patterns in distributed systems.
- Contributions to open-source projects, publications, or speaking engagements that demonstrate thought leadership in AI/ML are a plus.
WHO WE ARE
Zeta Global (NYSE: ZETA) is the AI-Powered Marketing Cloud that leverages advanced artificial intelligence (AI) and trillions of consumer signals to make it easier for marketers to acquire, grow, and retain customers more efficiently. Through the Zeta Marketing Platform (ZMP), our vision is to make sophisticated marketing simple by unifying identity, intelligence, and omnichannel activation into a single platform – powered by one of the industry’s largest proprietary databases and AI. Our enterprise customers across multiple verticals are empowered to personalize experiences with consumers at an individual level across every channel, delivering better results for marketing programs. Zeta was founded in 2007 by David A. Steinberg and John Sculley and is headquartered in New York City with offices around the world. To learn more, go to www.zetaglobal.com.
PEOPLE & CULTURE AT ZETA
Zeta considers applicants for employment without regard to, and does not discriminate on the basis of an individual’s sex, race, color, religion, age, disability, status as a veteran, or national or ethnic origin; nor does Zeta discriminate on the basis of sexual orientation, gender identity or expression.
We’re committed to building a workplace culture of trust and belonging, so everyone feels invited to bring their whole selves to work. We provide a forum for employees to celebrate, support and advocate for one another. Learn more about our commitment to diversity, equity and inclusion here: https://zetaglobal.com/blog/a-look-into-zetas-ergs/
ZETA IN THE NEWS!
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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.
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Data Scientist
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Who we are
Metropolis is an artificial intelligence company that uses computer vision technology to enable frictionless, checkout-free experiences in the real world. Today, we are reimagining parking to enable millions of consumers to just "drive in and drive out." We envision a future where people transact in the real world with a speed, ease and convenience that is unparalleled, even online. Tomorrow, we will power checkout-free experiences anywhere you go to make the everyday experiences of living, working and playing remarkable - giving us back our most valuable asset, time.
Who you are
We are looking for a highly motivated and analytical Data Scientist to join our growing data team. You will play a key role in extracting insights from large datasets, building predictive models, and supporting data-driven decision-making across departments.
What you'll do
- Collect, process, and analyze large datasets from multiple sources
- Build and deploy machine learning models to solve business problems
- Design and implement A/B tests and statistical analyses
- Collaborate with cross-functional teams (product, engineering, marketing) to define analytics requirements
- Communicate complex data insights in a clear and actionable manner to stakeholders
- Develop dashboards and visualizations to monitor key metrics
- Stay current with the latest trends and technologies in data science and AI
What we're looking for
- Bachelor’s and or Master’s degree in Computer Science, Mathematics, Statistics, or related field
- 4+ years of proven experience as a Data Scientist or Data Analyst
- Strong knowledge of Python/R and SQL
- Hands-on experience with machine learning frameworks (e.g., scikit learn, tensroflow, pytorch)
- Experience with big data tools (e.g., Spark, Hadoop)
- Familiarity with data visualization tools
- Strong analytical, problem-solving, and communication skills
While not required, these are a plus:
- Experience with cloud platforms preferably AWS (S3, Sagemaker, Airflow etc)
- Strong SQL skills, with experience in Snowflake, MySQL, and PostgreSQL
- Familiarity with data visualization tools (e.g., Tableau, Power BI, Looker)
3 Days in Office: Metropolis values in-person collaboration to drive innovation, strengthen culture, and enhance the Member experience. Our corporate team members hold to our office-first model, which requires employees to be on-site at least four days a week, fostering organic interactions that spark creativity and connection.
When you join Metropolis, you'll join a team of world-class product leaders and engineers, building an ecosystem of technologies at the intersection of parking, mobility, and real estate. Our goal is to build an inclusive culture where everyone has a voice and the best idea wins. You will play a key role in building and maintaining this culture as our organization grows. #LI-SR1 #LI-Onsite
Metropolis may utilize an automated employment decision tool (AEDT) to assess or evaluate your candidacy for employment or promotion. AEDTs are used to assist in assessing a candidate’s application relative to the required job qualifications and responsibilities listed in the job posting.
As part of this process, Metropolis retains data relevant to your candidacy, including personal information, for a period that is reasonably necessary for the use of the tool. If you are hired for the position, your data may become part of your employee records.
Metropolis Technologies is an equal opportunity employer. We make all hiring decisions based on merit, qualifications, and business needs, without regard to race, color, religion, sex (including gender identity, sexual orientation, or pregnancy), national origin, disability, veteran status, or any other protected characteristic under federal, state, or local law.
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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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Staff Engineer - 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 - Staff Engineer – Software Development.
Our SaaS platform serves enterprise customers with a reliable, secure, and scalable product built on modern microservices, event-driven data pipelines, and increasingly, AI-powered capabilities.
We are seeking a Staff Engineer – Software Engineering to join our SaaS Platform team. Staff Engineers at Aviatrix operate at the intersection of technical depth and cross-team influence. You will drive the design and delivery of complex backend systems — including AI-augmented data pipelines and agentic AI integrations — while raising the technical bar across the organization. This role is ideal for an engineer who is deeply technical, thrives on solving ambiguous problems, and is ready to shape both the platform’s architecture and the team’s engineering culture.
Position Responsibilities
Architecture & Technical Leadership
- Lead the architecture and delivery of complex backend platform features spanning multiple microservices; break down large, ambiguous projects into well-scoped sub-projects and guide senior engineers through execution.
- Define technical standards, patterns, and best practices for backend microservices development across the team — covering API design, service communication, data modeling, and reliability.
- Own the architectural design of AI-augmented data pipelines: integrating model inference, agentic workflows, and LLM-based processing steps into streaming and batch data flows on AWS.
- Evaluate and recommend agentic AI frameworks and tooling (such as LangChain, LlamaIndex, Amazon Bedrock Agents, or equivalent) for use in platform components; establish integration patterns the broader team can follow.
- Write and present comprehensive design documents and technical proposals that articulate complex problems, solution trade-offs, and long-term platform direction.
- Drive improvements to Aviatrix’s product and security posture, including contributions outside your immediate project area.
AI-Augmented Data Pipelines
- Design and implement data pipelines that incorporate AI/ML model inference as a first-class processing step, enabling intelligent enrichment, classification, anomaly detection, and summarization of platform telemetry and events.
- Architect agentic AI workflows that operate autonomously within data pipelines — orchestrating tool use, retrieval-augmented generation (RAG), and multi-step reasoning to drive platform automation.
- Integrate large language models (LLMs) and foundation models via managed APIs (Amazon Bedrock, OpenAI, Anthropic) and self-hosted inference endpoints into backend services and pipeline stages.
- Build robust prompt engineering and context management layers that make AI model calls reliable, observable, cost-efficient, and safe in a production SaaS context.
- Establish guardrails, evaluation frameworks, and monitoring strategies for AI components in pipelines — including output validation, hallucination detection, latency tracking, and cost controls.
- Collaborate with data and ML teams to define feature stores, embedding pipelines, vector database integrations (e.g., Amazon OpenSearch, pgvector), and model lifecycle management practices.
Backend & Microservices Engineering
- Design and implement high-performance, production-grade microservices in Golang using gRPC and REST; ensure services are secure, observable, and operationally resilient.
- Drive the design of event-driven architectures using AWS data pipeline services — Kinesis, MSK (Kafka), Glue, Step Functions, and EMR — to support real-time and batch processing at scale.
- Enforce strong security and networking practices: AWS VPC architecture, IAM least-privilege access, PrivateLink for private service connectivity, and encryption in transit and at rest.
- Lead platform-wide reliability initiatives: SLO definition, distributed tracing, structured logging, alerting, and chaos engineering practices.
- Conduct rigorous design and code reviews; set a high bar for correctness, testability, and operational readiness.
Team Influence & Collaboration
- Serve as a technical anchor for the team — raising engineering quality through mentorship, design guidance, and a culture of rigorous technical thinking.
- Collaborate with product management and leadership to align technical roadmap investments with business priorities and customer needs.
- Partner with senior engineers across teams to drive consistency in platform architecture and avoid redundant solutions.
- Provide expert guidance during escalations and critical production incidents; drive root-cause analysis and long-term remediation.
- Contribute to recruiting and interviewing; help define bar-raising standards for backend and AI engineering roles.
Requirements
Experience & Education
- 7–10+ years of professional software engineering experience, with a strong track record of technical leadership on backend systems.
- Bachelor’s degree in Computer Science, Engineering, or a related technical field (or equivalent practical experience).
- Demonstrated experience designing and operating SaaS or PaaS products at scale, with multi-tenancy and high-availability requirements.
- Strong foundation in data structures, algorithms, operating systems, and distributed systems.
- Experience working in fast-paced, high-growth technology companies with geographically distributed teams.
Backend & Microservices
- Strong proficiency in Golang; experience building production-grade gRPC-based microservices.
- Deep understanding of distributed systems: consistency, fault tolerance, service discovery, back-pressure, and distributed tracing.
- Expertise in RESTful and gRPC API design, with a strong sense of API contracts, versioning, and backward compatibility.
- Experience building event-driven architectures with message queue and streaming systems (Kafka/MSK, Kinesis, SQS/SNS).
- Strong understanding of elegant and robust system design; ability to evaluate and articulate key engineering trade-offs.
Agentic AI & LLM Integration
- Hands-on experience integrating large language models (LLMs) and foundation models into production backend systems via managed APIs or self-hosted inference.
- Practical knowledge of agentic AI concepts: tool use, autonomous multi-step reasoning, agent orchestration, and human-in-the-loop patterns.
- Experience with at least one agentic AI framework or platform (e.g., LangChain, LlamaIndex, Amazon Bedrock Agents, AutoGen, or similar).
- Familiarity with retrieval-augmented generation (RAG): embedding models, vector databases (OpenSearch, pgvector, Pinecone), and context retrieval strategies.
- Understanding of prompt engineering principles: structured prompts, few-shot examples, chain-of-thought reasoning, and output validation.
- Experience designing AI guardrails and evaluation pipelines to ensure reliability, safety, and cost-efficiency of LLM components in production.
Data Pipelines
- Proven experience designing and operating large-scale data pipelines for real-time streaming and batch workloads.
- Strong working knowledge of AWS data pipeline services: Amazon Kinesis (Data Streams & Firehose), AWS Glue, Amazon MSK, AWS Step Functions, and Amazon EMR.
- Ability to embed AI/ML inference steps — including LLM calls, embedding generation, and model scoring — as processing stages within data pipelines.
- Familiarity with pipeline observability: data lineage, quality monitoring, SLA management, and alerting.
- Experience with schema management, data quality enforcement, and data catalog practices (e.g., AWS Glue Data Catalog).
AWS & Cloud Infrastructure
- Deep experience with AWS as a primary cloud platform; strong understanding of high-availability, multi-AZ deployment patterns.
- Solid knowledge of AWS networking and security: VPC architecture, IAM roles and policies, AWS PrivateLink, Transit Gateway, and security groups.
- Proficiency with Kubernetes (EKS), including workload scheduling, RBAC, networking (CNI), and cluster operations.
- Experience with infrastructure-as-code (Terraform, CDK, or CloudFormation) and CI/CD pipelines for cloud-native backend services.
- Familiarity with Amazon Bedrock or equivalent managed AI/ML platforms for model deployment and inference at scale.
Nice to Have
- Experience fine-tuning or adapting foundation models for domain-specific tasks.
- Familiarity with ML frameworks (PyTorch, HuggingFace Transformers) and model serving infrastructure (SageMaker, TorchServe).
- Background in network security, cloud networking, or SASE/SD-WAN technologies.
- Experience with multi-cloud environments (Azure, GCP) alongside AWS.
- Contributions to open-source AI, data engineering, or cloud-native projects.
Interpersonal & Communication
- Excellent written and verbal communication; able to produce clear technical documents and present confidently to engineering and product leadership.
- Demonstrated ability to lead through influence, build consensus across teams, and drive outcomes without direct authority.
- Team player who thrives in collaborative, geographically distributed environments and startup-paced cultures.
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
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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?
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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.
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Principal 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.
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AI/ML Solution Architect (India)
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We seek a highly skilled and experienced Lead Machine Learning Engineer with a PhD and extensive expertise in large language models (LLMs), multi-agent systems, and flow engineering. The ideal candidate will not only have a strong technical background but also the drive to mentor and educate our machine learning team and advocate for the adoption of new and emerging technologies.
WHAT YOU'LL DO
- Drive innovation as a technical leader, build strong relationships and ensure the successful development and deployment of LLMs
- Collaborate with other teams and stakeholders to integrate our LLMs into various applications and workflows, providing technical guidance and support as needed
- Develop and execute comprehensive testing strategies to ensure the performance and effectiveness of our LLMs in various applications and workflows
- Design and develop novel LLM architectures that meet specific business requirements or identify opportunities for improvement in existing models
- Explore new techniques, algorithms, and tools to stay ahead of the curve
- Identify and curate high-quality datasets that align with business objectives and are suitable for training, validating, and testing LLMs
- Explore alternative data sources, create synthetic data, and develop custom data generation techniques
WHAT YOU'LL NEED
- PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related field
- Proven experience in developing and deploying large language models (LLMs) and a deep understanding of their architectures and applications
- Strong background in multi-agent systems, flow engineering, and related AI technologies
- Demonstrated ability to lead and mentor a team of machine learning engineers and data scientists
- Excellent communication and presentation skills, with the ability to articulate complex concepts clearly
- Professional experience developing Python libraries for machine-learning applications. Strong background in Pytorch, HuggingFace, Langchain/LlamaIndex and other ML libraries.
- Strong problem-solving skills and the ability to think critically and creatively
- A track record of published research in reputable journals or conferences is a plus
ABOUT US
Born in 2001, Code and Theory is a digital-first creative agency that sits at the center of creativity and technology. We pride ourselves on not only solving consumer and business problems, but also helping to establish new capabilities for our clients. With a global client roster of Fortune 100s and start-ups alike, we crave the hardest problems to solve. We have teams distributed across North America, South America, Europe, and Asia. The Code and Theory global network of agencies is growing and includes Kettle, Instrument, Left Field Labs, Create Group, Current, and TrueLogic.
Striving never to be pigeonholed, we work across every major category: from tech to CPG, financial services to travel & hospitality, government and education to media and publishing. We value the collaboration with our client partners, including but not limited to Adidas, Amazon, Con Edison, Diageo, EY, J.P. Morgan Chase, Lenovo, Marriott, Mars, Microsoft, Thomson Reuters, and TikTok.
The Code and Theory network is comprised of nearly 2,000 people with 50% engineers and 50% creative talent. We’re always on the lookout for smart, driven, and forward-thinking people to join our team.
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Senior Engineer, AI/ML (India)
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We seek a highly skilled and experienced Senior Machine Learning Engineer with extensive expertise in multimodal generative AI models, cross-modal architectures, and multimodal fusion techniques. The ideal candidate will not only have a strong technical background spanning text, vision, audio, and video modalities, but also the drive to mentor, educate, and advocate for the adoption of new and emerging technologies.
WHAT YOU'LL NEED
- 5+ years experience in machine learning engineering, with at least 1 year focussed on generative AI or multimodal systems
- Strong hands-on experience with multimodal AI models including text-to-image, image-to-text, or other cross-modal applications
- Deep practical knowledge of either computer vision or NLP, with demonstrated ability to work across modalities
- Proficiency with generative model architectures such as diffusion models, transformer-based generative models, or GANs
- Strong programming skills in Python with extensive experience in PyTorch and HuggingFace ecosystem (Transformers, Diffusers, Accelerate)
- Experience with cloud ML platforms (AWS SageMaker, GCP Vertex AI, Azure ML)
- Proven track record of deploying ML models to production with understanding of model optimization, serving, and monitoring
- Strong problem-solving skills and the ability to think critically and creatively about novel multimodal applications
NICE TO HAVE
- A track record of published research in reputable journals or conferences (NeurIPS, ICML, CVPR, ICCV, etc.)
- Understanding of prompt engineering and guidance techniques for generative models
- Experience with model fine-tuning, LoRA, and efficient adaptation methods
ABOUT US
Born in 2001, Code and Theory is a digital-first creative agency that sits at the center of creativity and technology. We pride ourselves on not only solving consumer and business problems, but also helping to establish new capabilities for our clients. With a global client roster of Fortune 100s and start-ups alike, we crave the hardest problems to solve. We have teams distributed across North America, South America, Europe, and Asia. The Code and Theory global network of agencies is growing and includes Kettle, Instrument, Left Field Labs, Create Group, Current, and TrueLogic.
Striving never to be pigeonholed, we work across every major category: from tech to CPG, financial services to travel & hospitality, government and education to media and publishing. We value the collaboration with our client partners, including but not limited to Adidas, Amazon, Con Edison, Diageo, EY, J.P. Morgan Chase, Lenovo, Marriott, Mars, Microsoft, Thomson Reuters, and TikTok.
The Code and Theory network is comprised of nearly 2,000 people with 50% engineers and 50% creative talent. We’re always on the lookout for smart, driven, and forward-thinking people to join our team.
Ready to apply?
Apply to Code and Theory
Who We Are:
CrashPlan® provides cyber-ready data resilience and governance in a single platform for organizations whose ideas power their revenue. With its comprehensive backup and recovery capabilities for data stored on servers, on endpoint devices, and in SaaS applications, CrashPlan’s solutions are trusted by entrepreneurs, professionals, and businesses of all sizes worldwide. From ransomware recovery and breaches to migrations and legal holds, CrashPlan’s suite of products ensures the safety and compliance of your data without disruption.
We are looking for an experienced Senior Developer with a strong foundation in backend engineering and a growing interest in AI/ML to help shape the next generation of our enterprise SaaS platform. This role is primarily focused on designing, developing, and maintaining scalable Java-based solutions for data resiliency, ransomware defence, and data security — while also contributing to and gradually leading our AI initiatives.
You will work closely with our product, engineering, and DevOps teams to build core platform capabilities, and also lead a small AI team to integrate agentic capabilities into our product. This is not a pure AI research role; we want someone who remains deeply connected to the core product and brings AI as a force multiplier, not as a separate discipline.
Core Engineering:
- Design, develop, and maintain high-performance, scalable Java-based enterprise applications
- Build and enhance backend services, APIs, and microservices architecture
- Write clean, efficient, and maintainable code following best practices and coding standards
- Troubleshoot, debug, and optimize application performance and reliability
- Ensure application security, scalability, and high availability
- Support continuous integration and deployment processes
- Participate in architecture discussions and contribute to technical design decisions
AI Integration & Leadership:
- Lead a small AI team to design and deliver AI-powered features within our core platform
- Integrate AI/ML capabilities — such as automated reporting, anomaly detection, smart alerts, and incident workflows — into existing Java-based services
- Evaluate and adopt emerging AI tools and frameworks (e.g. LLMs, RAG, Agentic AI) where they add practical value to the product
- Ensure AI solutions are production-grade: secure, explainable, performant, and aligned with business goals
- Act as a bridge between AI experimentation and core product engineering — keeping AI grounded in real product impact
Collaboration & Mentorship:
- Collaborate closely with Product Management, Engineering, QA, and DevOps teams, including remote teams
- Conduct code reviews and mentor junior developers
- Contribute to a culture of technical excellence, speed, and ownership
- 10+ years of experience in software development for enterprise applications
- Strong proficiency in Java, Spring Boot, and Microservices architecture
- Hands-on experience with Apache Kafka for building scalable, real-time data pipelines and event-driven microservices
- Experience building RESTful APIs and distributed systems
- Good understanding of databases (SQL/NoSQL) and data modelling concepts
- Experience with cloud platforms (AWS/Azure/GCP)
- Familiarity with containerization technologies such as Docker and Kubernetes
- Strong understanding of software design patterns and system architecture
- Experience working in Agile development environments
AI/ML (Hands-on Experience Preferred)
- Practical experience integrating AI/ML models or services into production Java applications
- Familiarity with Python and AI/ML frameworks (TensorFlow, PyTorch, or equivalent) is a strong plus
- Understanding of LLM integrations, RAG pipelines, or agent-based AI systems
- Knowledge of MLOps practices and model lifecycle management is advantageous
- Exposure to AI system design and scalable AI architectures
Leadership
- Demonstrated ability to lead small technical teams or work streams
- Strong analytical, problem-solving, and communication skills
- Ability to collaborate effectively with cross-functional and distributed teams
Work Environment & Expectations:
- Based in Bangalore, working from the HSR Layout office
- Willingness to work alternate Saturdays
- Comfortable with dynamic workloads and flexible work hours, typical of a startup environment
- Speed, adaptability, and ownership mindset are essential
CrashPlan values workplace diversity and ensuring an environment of mutual respect. Employment opportunities are available to all applicants without regards to race, color, creed, religion, sex, national origin, age, marital status, veteran status, sexual orientation, gender identity or expression, disability, genetic information, or any other category protected by law. We believe that diversity and inclusion are critical to our success, and we seek to recruit, develop, and retain the most talented people from a diverse candidate pool. We are proud to be an equal opportunity employer.
Ready to apply?
Apply to CrashPlanSenior Machine Learning Engineer
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Want to build the next generation of AI-powered analytics and intelligent agents for observability and security use cases? Passionate about leveraging cutting-edge machine learning, large language models, and GPU-accelerated inference to transform how organizations understand and act on their logs data? Come talk with us!
As a Senior Machine Learning Engineer, you’ll build the intelligence behind the next generation of agentic AI systems that reason over massive, heterogeneous log data. You’ll combine machine learning, prompt engineering, context engineering and rigorous evaluation to create autonomous AI agents that help organizations understand and act on their data in real time.
You’ll be part of a small, high-impact team shaping how AI agents understand complex machine data. This is an opportunity to work on cutting-edge LLM infrastructure and contribute to defining best practices in context engineering and AI observability.
Location: Noida/ Bengaluru (Hybrid)
Responsibilities
- Design, implement, and optimize agentic AI components, including tools, memory management, and prompts.
- Develop and maintain golden datasets by defining sourcing strategies, working with data vendors, and ensuring quality and representativeness at scale.
- Prototype and evaluate novel prompting strategies and reasoning chains for model reliability and interpretability.
- Collaborate cross-functionally with product, data, and infrastructure teams to deliver end-to-end AI-powered insights.
- Operate autonomously in a fast-paced, ambiguous environment - defining scope, setting milestones, and driving outcomes.
- Ensure reliability, performance, and observability of deployed agents through rigorous testing and continuous improvement.
- Maintain a strong bias for action—delivering incremental, well-tested improvements that directly enhance customer experience.
Required Qualifications
- B.Tech, M.Tech, or Ph.D. in Computer Science, Data Science, or a related field.
- 6+ years of hands-on industry experience with demonstrable ownership and delivery.
- Strong understanding of machine learning fundamentals, data pipelines, and model evaluation.
- Proficiency in Python and ML/data libraries (NumPy, pandas, scikit-learn); familiarity with JVM languages is a plus.
- Working knowledge of LLM core concepts, prompt design, and agentic design patterns.
- Experience with distributed systems and dealing with large amounts of data.
- Strong communication skills and a passion for shaping emerging AI paradigms.
Desired Qualifications
- Experience leading a team of engineers.
- Prior experience building and deploying AI agents or LLM applications in production.
- Familiarity with modern agentic AI frameworks (e.g., LangGraph, LangChain, CrewAI).
- Experience with ML infrastructure and tooling (PyTorch, MLflow, Airflow, Docker, AWS).
- Exposure to LLM Ops - infrastructure optimization, observability, latency, and cost monitoring.
About Us
Sumo Logic, Inc. empowers the people who power modern, digital business. Sumo Logic enables customers to deliver reliable and secure cloud-native applications through its Sumo Logic SaaS Analytics Log Platform, which helps practitioners and developers ensure application reliability, secure and protect against modern security threats, and gain insights into their cloud infrastructures. Customers worldwide rely on Sumo Logic to get powerful real-time analytics and insights across observability and security solutions for their cloud-native applications. For more information, visit www.sumologic.com.
Sumo Logic Privacy Policy. Employees will be responsible for complying with applicable federal privacy laws and regulations, as well as organizational policies related to data protection.
Ready to apply?
Apply to Sumo LogicHeadquartered in Los Altos, CA. Backed by SAIGroup.
Learn more about JazzX AI:
Website: https://jazzx.ai
LinkedIn: https://www.linkedin.com/company/jazzx-ai
Learn more about SAIGroup:
Website: https://saigroup.ai
Solutions Architect
Role Overview
As Solutions Architect you operate at the intersection of deep technical leadership and high-stakes client engagement. You will:
- Own solution architecture and technical delivery for marquee customers, ensuring JazzX’s AGI platform unlocks measurable business value.
- Guide multi-disciplinary squads (product, research, engineering, and customer success) from discovery through full production rollout.
- Shape platform roadmap with field feedback, driving features that accelerate time-to-value and differentiate JazzX in the market.
You are equally comfortable white-boarding LLM retrieval strategies, optimising prompt chains, troubleshooting Kubernetes deployments, or presenting to a C-suite audience.
Key Responsibilities
|
Focus Area |
What You’ll Do |
|
Solution Architecture |
• Design end-to-end architectures that integrate JazzX’s AGI services (LLM orchestration, vector search, tool-calling agents) with client data sources, APIs, and security controls. |
|
Technical Delivery & GTM Execution |
• Run the full delivery lifecycle—discovery, PoC, pilot, production, and hyper-care—balancing speed with robust engineering practices. |
|
Client Engagement & Stakeholder Management |
• Translate business problems into AGI solutions, articulate trade-offs, and build trusted-advisor relationships with technical and non-technical leaders. |
|
Technical Leadership & Mentorship |
• Coach engineers across JazzX in AGI best practices, code quality, security, and DevOps. |
|
Innovation & Platform Influence |
• Evaluate emerging AI/ML and tooling (e.g., AutoGen, RAG pipelines, WASM inferencing) and pilot them in customer contexts. |
Qualifications
Must-Have
- 10–12 years of software engineering experience, 5+ in staff/principal or solution-architect roles.
- Proven record delivering large-scale, low-latency distributed systems (Python, Java, Go, or C++).
- Hands-on with LLM / AI frameworks (LangChain, LlamaIndex, PyTorch, TensorFlow) and productionising ML pipelines.
- Expertise integrating REST/GraphQL APIs, streaming platforms (Kafka), SQL & NoSQL stores, and vector DBs.
- Outstanding client-facing communication, executive-level presentation, and stakeholder-management skills.
Nice-to-Have
- Masters or PhD in AI/Data Science/Computer Science
- Experience shipping RAG or agent-based AI systems in regulated industries.
- Nice to have certifications in cloud architecture, data engineering, or security (e.g., AWS SA-Pro, CKA).
- Background in professional-services, forward-deployed engineering, or AI platform product management.
Attributes
- Empathy & Ownership: You listen carefully to user needs and take full ownership of delivering great experiences.
- Startup Mentality: You move fast, learn quickly, and are comfortable wearing many hats.
- Detail-Oriented: You care about the little things
- Mission-Driven: You want to solve important, high-impact problems that matter to real people.
- Team-Oriented: Low ego, collaborative, and excited to build alongside highly capable engineers, designers, and domain experts.
Travel:
This position requires the ability to travel to client sites as needed for on-site deployments and collaboration. Travel is estimated at approximately 30–40% of the time (varying by project), and flexibility is expected to accommodate key client engagement activities.
Why Join JazzX AI:
What draws people to JazzX AI is the opportunity to build something truly foundational.
We are at the beginning of a new era — one where enterprise systems will no longer be static tools, but dynamic collaborators that learn, reason, and evolve alongside the people who use them. At JazzX AI, you’ll help build a platform that redefines how work happens in the AGI era.
JazzX AI brings together vision, deep technology, and purpose. This is not about experimenting with AI features; it’s about turning the promise of AGI into practical, auditable, and human-aligned systems that enterprises can trust and rely on at scale. The work here directly impacts productivity, efficiency, and decision-making in complex, real-world environments.
If you’re motivated by building systems that matter — systems that combine intelligence with responsibility — JazzX AI offers the chance to do that work at a deeper level, with real ownership and lasting impact.
Ready to apply?
Apply to JazzX AIAbout 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.
Summary:
Tekion seeks an exceptionally talented and seasoned Senior Staff Applied Scientist to architect the future of our AI-driven solutions. The incumbent will assume a pivotal role in our organization, providing the strategic and technical stewardship necessary to translate cutting-edge research into tangible business value. The ideal candidate is a first-principles thinker, adept at navigating ambiguity, and possesses the intellectual curiosity to formulate and solve complex, unstructured problems. This is a seminal opportunity to influence the trajectory of our AI strategy and deliver transformative solutions at an enterprise scale.
Key Responsibilities:
- Strategic Direction: Architect and execute the strategic vision for applied AI and Machine Learning within Tekion, ensuring rigorous alignment with overarching business objectives and industry challenges.
- Innovation & Research Leadership: Steer the R&D roadmap by identifying and capitalizing on emergent technological opportunities. Drive innovation through the ideation and implementation of novel, scientifically-grounded solutions.
- Stakeholder Alignment: Serve as the principal technical liaison between the R&D organization and executive stakeholders, ensuring technical strategies are congruent with business imperatives.
- Cross-Functional Execution: Lead collaborations with product, engineering, and business units to define, develop, and integrate sophisticated machine learning systems into core products and services.
- Scientific Contribution: Contribute to the broader scientific community through publications in premier academic conferences and journals, enhancing Tekion's position as a center of innovation.
- Mentorship & Talent Development: Mentor and cultivate a culture of scientific rigor and innovation among applied scientists, guiding project execution and fostering professional growth.
- Impact Quantification: Establish robust frameworks for model evaluation and performance measurement. Quantify and articulate the business impact of machine learning initiatives to executive leadership.
- Governance & Best Practices: Institute and govern best practices for the entire machine learning lifecycle, including model development, validation, deployment, and monitoring, while championing ethical and responsible AI
Core Competencies & Technical Expertise
The successful candidate will demonstrate mastery in the following areas:
- Foundational Expertise: Deep, theoretical and practical expertise in Machine Learning, Deep Learning, Causal Inference, and Explainable AI.
- Statistical Rigor: Advanced proficiency in applied probability and statistics to derive and validate insights from complex, high-dimensional data.
- Deep Learning:
- Expert-level proficiency with frameworks such as TensorFlow, Keras, and PyTorch.
- Extensive experience implementing advanced neural network architectures.
- Practical application of Computer Vision (e.g., OpenCV) and Natural Language Processing (e.g., spaCy) methodologies.
- Large Language Models (LLMs): Demonstrated experience with Large Language Models, including advanced prompt engineering, fine-tuning, and deployment for specific business applications.
- Technical Proficiencies:
- Advanced programming skills in Python and mastery of SQL. Familiarity with distributed computing frameworks (e.g., Spark) is advantageous.
- Proficiency with cloud computing platforms (GCP, Azure, AWS).
- Expertise in experimental design (A/B testing, causal inference).
- Proficient in version control systems (Git).
Required Qualifications
- An advanced degree (Ph.D. or M.S. preferred) in a quantitative discipline such as Computer Science, Statistics, Operations Research, Physics, or a related field.
- A minimum of 10+ years of post-academic experience in applied science or quantitative research roles, with a demonstrable history of translating complex models into tangible business value.
- A distinguished track record of solving difficult, business-critical problems using a scientific, data-driven approach.
- Proven experience in programming, data manipulation, and building models in a business context.
- Sophisticated data visualization and presentation skills, with the ability to distill complex analytical results into clear, actionable insights for diverse audiences.
Ideal Candidate Profile
- A profound intellectual curiosity and a systematic, first-principles approach to problem-solving.
- Domain expertise in the automotive industry or related fields such as finance or enterprise SaaS is highly desirable.
- Experience in specialized areas such as Recommendation Engines or advanced NLP is preferred.
- Exceptional communication and presentation capabilities, with a proven ability to distill complex technical concepts for executive-level audiences.
- A demonstrated ability to work collaboratively and effectively lead initiatives across multi-disciplinary teams.
- A commitment to continuous personal and team development within a collaborative, high-performance culture.
Address:
Bangalore Office
Tekion India Private Limited
6th, 7th & 8th Floor, Helium, Bagmane Solarium City, Doddanekkundi Village, KR Puram Hobli, East Taluk, Bangalore - 560037
Chennai Office
Embassy Splendid Zone, Block 2, 9th floor, Velan Nagar, Arulmurugan Nagar, Old Pallavaram, Chennai, Tamil Nadu 600043
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.
Ready to apply?
Apply to Tekion
Senior Data Scientist
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ABOUT TIDE
At Tide we help SMEs save time (and money) in the running of their businesses by not only offering business accounts and related banking services, but also a comprehensive set of highly usable and connected administrative solutions from invoicing to accounting.
Tide is transforming the small business banking market with over 1.8 million members globally across the UK, India, Germany and France.
Using advanced technology, all solutions are designed with SMEs in mind. With quick onboarding, low fees and innovative features, we thrive on making data-driven decisions to serve our mission: to help SMEs save both time (and money) so they can get back to doing what they love.
Tide facts:
- Tide is available for UK, Indian, German and French SMEs
- Over 1.8 million members: 800,000 UK and 1,000,000 in India and growing rapidly
- Over $300 million raised in funding
- Over 2,500 Tideans globally - we’re diversity champions!
- We have offices in Central London, with a member support and technology centre in Sofia, Bulgaria, technology centres in Serbia, Romania, Lithuania and Hyderabad and offices in Gurugram and New Delhi, and in Berlin, Paris and Luxembourg.
ABOUT THE ROLE
You are a seasoned Data Scientist, passionate about building robust, real-time machine learning solutions to combat financial crime. Working within the Risk & Fraud Team, you will leverage advanced statistical modeling and machine learning to detect, prevent, and adapt to evolving fraud threats. You thrive on solving complex problems with highly imbalanced data and delivering tangible risk reduction impact in a fast-paced environment.
You strongly believe in agile principles and use them to deliver value incrementally. You are eager to learn about new methodologies and practices and apply them directly in your work.
As a Senior Data Scientist you’ll be:
- Model Development & Risk Mitigation: Design, develop, and implement advanced ML/Statistical models to predict and prevent various fraud typologies. Focus on driving impact by optimising costs and reducing risk using ML/Stats models.
- Specialised Data Handling: Employ advanced techniques to manage and model highly imbalanced, large datasets characteristic of the fraud domain.
- Adaptive Systems: Build and maintain models that can quickly adapt to new and evolving fraud typologies and emerging threats.
- Real-Time MLOps: Develop, optimise, and deploy ML models for real-time/low-latency inference in production settings.
- Data & Feature Engineering: Utilize, enrich, and contribute to the feature store ecosystem, ensuring high-quality, scalable features for risk models.
- Performance Monitoring: Implement and maintain robust drift monitoring and model performance tracking to ensure deployed models remain effective and stable.
- Collaboration: Work closely with ML Engineers to productionize models leveraging AWS/GCP tech stack, and collaborate with Business and Product teams to understand requirements and solutionise data products.
- Exploration: Identify creative solutions in order to build relevant training data sets and explore the value of new data structures like knowledge graphs for relational fraud detection.
WHAT ARE WE LOOKING FOR
- You have 6+ years of experience in Software Development or Machine Learning, with a strong emphasis on practical model development and deployment.
- You are Strong in Python and have expert knowledge with Machine Learning tools/libraries (e.g., scikit-learn, statmodels, TensorFlow, Keras, or PyTorch).
- You have experience with big-data technologies such as Spark, SparkML, Hadoop etc. and have handled large data in a distributed processing environment. AWS, GCP, or Azure (anyone) cloud knowledge is preferred.
- You are proficient in ML training, optimising, feature selection and engineering, hyperparameter tuning and have knowledge about trade-offs in using different algorithms.
- You have demonstrated experience in developing and deploying a variety of ML-algorithms (e.g., logistic regressions, boosted trees, neural networks) that work in real-time settings.
- You have a good working knowledge with basic data table operations (SQL etc.), and data transform in the warehouse (dbt etc.).
- You are comfortable with ambiguity and are a self-starter—you take initiative in spotting opportunities and finding ways to solve challenges with data.
- Familiarity with Financial Services and Fintech space is preferred.
- You will be helping optimise all aspects of our sales funnel including finding ways to increase lead quality, reduce our cost of acquisition, optimise lead allocation, and improve the likelihood of successful lending outcomes for our members
Highly Desirable Skills:
- Exposure to Cost-Sensitive Learning techniques, where the economic impact of prediction errors is a key optimization factor.
- A decent idea and practical exposure to MLOps principles (e.g., model versioning, continuous integration/deployment for ML).
- Experience with Drift monitoring tools and frameworks.
- Exposure to Knowledge Graphs or graph database applications.
- Competitive Compensation - competitive salary and share options
- Time Off – Generous annual leave on top of bank holidays.
- Parental Leave – Paid maternity, paternity, and adoption leave to support your family journey.
- Sabbatical – Extended unpaid and paid leave options after completing milestone years with Tide.
- Health Insurance – Private family insurance with additional OPD coverage and top-up options.
- Life & Accident Cover – Comprehensive accidental and life insurance protection.
- Mental Wellbeing – Access to therapy sessions, courses, meditations, and workshops.
- Volunteering & Development Days – Paid days annually for volunteering or personal growth.
- Learning & Development – Annual budget for books, courses, coaching, and more.
- WOO (Work Outside the Office) – Work from abroad for up to 90 days annually.
- Home Office Setup – Contribution towards setting up your home office
- Laptop Ownership – Keep your old laptop and get a new one when it’s time for a replacement.
- Snacks & Meals – Office perks with snacks, coffee, tea, and lunch (location dependent).
TIDEAN WAYS OF WORKING
At Tide, we champion a flexible workplace model that supports both in-person and remote work to cater to the specific needs of our different teams.
While remote work is supported, we believe in the power of face-to-face interactions to foster team spirit and collaboration. Our offices are designed as hubs for innovation and team-building, where we encourage regular in-person gatherings to foster a strong sense of community.
TIDE IS A PLACE FOR EVERYONE
At Tide, we believe that we can only succeed if we let our differences enrich our culture. Our Tideans come from a variety of backgrounds and experience levels. We consider everyone irrespective of their ethnicity, religion, sexual orientation, gender identity, family or parental status, national origin, veteran, neurodiversity or differently-abled status. We celebrate diversity in our workforce as a cornerstone of our success. Our commitment to a broad spectrum of ideas and backgrounds is what enables us to build products that resonate with our members’ diverse needs and lives.
We are One Team and foster a transparent and inclusive environment, where everyone’s voice is heard.
At Tide, we thrive on diversity, embracing various backgrounds and experiences. We welcome all individuals regardless of ethnicity, religion, sexual orientation, gender identity, or disability. Our inclusive culture is key to our success, helping us build products that meet our members' diverse needs. We are One Team, committed to transparency and ensuring everyone’s voice is heard.
- Tide does not charge any fees at any stage of the recruitment process.
- All official Tide job opportunities are listed exclusively on our Careers Page and applications should be submitted through this channel.
- Communication from Tide will only come from an official @tide.co email address.
- Tide does not work with agencies or recruiters without prior formal engagement, and we do not authorize third parties to make job offers on our behalf.
If you are contacted by anyone misrepresenting Tide or requesting payment, please treat it as fraudulent and report it to us immediately at talent@tide.co
Your safety and trust are important to us, and we are committed to ensuring a fair and transparent recruitment process.
Tide leverages AI to enhance our hiring experience. You can read more about how we use AI in our recruitment process in our AI Policy.
Your personal data will be processed by Tide for recruitment purposes and in accordance with Tide's Recruitment Privacy Notice.
Ready to apply?
Apply to Careers at TideHeadquartered in Los Altos, CA. Backed by SAIGroup.
Learn more about JazzX AI:
Website: https://jazzx.ai
LinkedIn: https://www.linkedin.com/company/jazzx-ai
Learn more about SAIGroup:
Website: https://saigroup.ai
Staff Software Development Engineer
As a Staff Software Development Engineer at JazzX AI, you'll define the technical vision for our enterprise AI platform, mentor senior engineers, and oversee the design, development, and deployment of critical AI, software and infra services and components. You'll be responsible for ensuring the platform's scalability, reliability, security and observability.
What You Will Do
Design and Architect Scalable Solutions:
- Lead the design and development of high-performance, scalable services and components for our enterprise AI platform using a cloud-first, cloud-agnostic approach with world class AI capabilities, scalability, security, privacy and operability.
- Champion a cloud-first, cloud-agnostic approach to ensure platform versatility, scalability, and future-proof architecture.
- Champion innovative AI and software design patterns and best practices to ensure code maintainability, reusability, and testability.
- Contribute to the platform's technical direction by staying up to date on emerging AI technologies, cloud design patterns and user experience methodologies.
Collaborative Innovation:
- Foster a collaborative environment by working closely with cross-functional teams (AI/research engineers, software engineers, architects, product managers, and designers) to translate complex platform and product requirements into elegant, scalable, and modular AI, software and infrastructure components.
- Foster a collaborative and inclusive environment by effectively communicating technical concepts and design decisions across diverse audiences.
- Provide mentorship and guidance to junior engineers, fostering their growth and development.
Driving Operational Excellence:
- Oversee the seamless integration of components into the platform, ensuring efficient operation, reliability, and a dependable user experience for both customers and partners.
- Champion DevOps and AIOps best practices for AI services, maintainability, performance optimization, and observability.
Requirements
- Minimum 10+ years of experience designing, building, and operating cloud-native applications at scale. Expertise in container orchestration frameworks like Kubernetes and containerization technologies like Docker. Expertise in AI/ML/data capabilities, platforms, frameworks and tools.
- Proven track record deploying and managing cloud environments using Infrastructure as Code (IaC) tools like Terraform, Ansible, or CloudFormation.
- Experience in designing and implementing highly available, scalable, and fault-tolerant systems.
Development Lifecycle:
- End-to-end ownership of the entire software development lifecycle (SDLC) for complex enterprise platforms and products. This includes experience in design, prototyping, development (including unit, integration, and end-to-end testing), deployment, and ongoing operations.
Technical Skills:
- Mastery of essential software development principles with a focus on clean code, design patterns, and best practices.
- In-depth expertise in at least two of the following programming languages: Python, Java, JavaScript, Golang, or C++.
- Solid understanding of distributed systems concepts and experience with distributed tracing tools.
AI/ML Experience:
- Demonstrated experience in building, deploying, and managing Machine Learning (ML) and Artificial Intelligence (AI) platforms and services. Familiarity with MLOps practices, frameworks (TensorFlow, PyTorch), and tools is a plus
- Familiarity with modern LLMs and AI agent frameworks like LangChain, LlamaIndex , AutoGen etc. is a strong plus
Why Join JazzX AI:
What draws people to JazzX AI is the opportunity to build something truly foundational.
We are at the beginning of a new era — one where enterprise systems will no longer be static tools, but dynamic collaborators that learn, reason, and evolve alongside the people who use them. At JazzX AI, you’ll help build a platform that redefines how work happens in the AGI era.
JazzX AI brings together vision, deep technology, and purpose. This is not about experimenting with AI features; it’s about turning the promise of AGI into practical, auditable, and human-aligned systems that enterprises can trust and rely on at scale. The work here directly impacts productivity, efficiency, and decision-making in complex, real-world environments.
If you’re motivated by building systems that matter — systems that combine intelligence with responsibility — JazzX AI offers the chance to do that work at a deeper level, with real ownership and lasting impact.
Ready to apply?
Apply to JazzX AI
Senior Machine Learning Engineer - NLP
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About Us
Observe.AI is the AI Agents platform for customer experience, designed to help organizations deliver faster, smarter, and more efficient customer service at scale. The platform enables businesses to deploy specialized AI agents that autonomously execute work across the full CX lifecycle—from handling customer conversations to supporting frontline teams and optimizing operations.
Each AI agent is purpose-built for a specific role, equipped to understand context, make decisions, take action, and continuously improve outcomes. This allows organizations to increase resolution speed, elevate service quality, and reduce operational costs while empowering your frontline team to focus on higher-value work.
Built on a CX-native foundation, Observe.AI helps leading brands like DoorDash, Affordable Care, Signify Health, and Verida improve customer satisfaction, boost agent productivity, and deliver consistent, scalable performance across every customer interaction.
Why Join Us
At our core, we are shaping how AI transforms real-world challenges in the contact center space. As part of our world-class ML team, you’ll work on developing cutting-edge LLM-powered solutions & Agentic AI, building end-to-end processing pipelines, and handling production challenges at scale—millions of interactions daily—while shaping the future of AI-powered contact centers.
If you are truly an engineer at heart, excited about turning breakthroughs in multi-agent systems, LLMs, NLP, and ML into practical outcomes through applied research, and building scalable production systems to create real product impact, you will feel right at home at Observe.AI. You’ll also have the opportunity to publish in top conferences, and influence Observe.AI’s product and platform strategy.
Beyond the tech, you’ll join a collaborative, mission-driven culture where innovation, impact, and fun go hand in hand. We value curiosity, collaboration, and the courage to push boundaries.
What you’ll be doing
- Design & develop state-of-the-art LLM-powered AI capabilities and Agentic AI/ Multi-agent systems end-to-end, from ideation to production for Observe.AI’s product offerings, in a fast-paced startup environment.
- Work with cutting-edge tools and technologies in Machine Learning, Deep Learning & Natural Language Processing, including LLMs and LLM-powered technologies/ paradigms, including Agentic AI.
- Build/ maintain highly scalable production systems that power AI capabilities on Observe.AI product/ platform.
- Optimize ML models and processing pipelines for performance, cost-effectiveness, and scale.
- Work with a world-class ML team in building exciting stuff, mentor juniors, and influence peers/ stakeholders.
- Collaborate cross-team with engineers, product managers, customer-facing teams, and customers to understand pain points and business opportunities to build the right solution for the right problem.
- Keep up-to-date with the latest ML/ DL/ NLP literature and influence the technological evolution of Observe.AI platform.
- Contribute to the community through tech blogs and publishing papers in ML/ NLP conferences like EMNLP, ACL, etc.
What you’ll bring to the role
- Bachelor’s or Master’s degree in Computer Science or related disciplines from a top-tier institution with exposure to ML/ DL/ NLP/ NLU.
- An engineering mindset with the competencies of an applied scientist.
- 3+ years of industry experience in building large-scale NLP/ NLU systems, with recent experience in building LLM-powered applications and Agentic systems.
- Strong understanding of the fundamentals of ML and NLP/ NLU, and practical aspects of building ML systems in production; backed by extensive hands-on experience in building/ scaling customer-facing ML/ NLP/ NLU applications.
- Good understanding of recent advances in building LLM-powered applications, and multi-agent systems at scale.
- Excellent implementation skills in Python and Machine Learning Frameworks such as Pytorch, Tensorflow, HuggingFace, etc., and deploying/ maintaining scalable machine learning systems in production.
- Ability to provide thought leadership in one or more technical areas of interest to Observe.AI, and influence product development
- Excellent communication, collaboration skills, and presentation skills.
- Experience with Spoken Language Understanding is a plus
- Published papers in top NLP/ NLU conferences or workshops are a plus
- Relevant open-source contributions are a plus.
Perks & Benefits
- Excellent medical insurance options and free online doctor consultations
- Yearly privilege and sick leaves as per Karnataka S&E Act
- Generous holidays (National and Festive) recognition and parental leave policies
- Learning & Development fund to support your continuous learning journey and professional development
- Fun events to build culture across the organization
- Flexible benefit plans for tax exemptions (i.e. Meal card, PF, etc.)
Our Commitment to Inclusion and Belonging
Observe.AI is an Equal Employment Opportunity employer that proudly pursues and hires a diverse workforce. Observe AI does not make hiring or employment decisions on the basis of race, color, religion or religious belief, ethnic or national origin, nationality, sex, gender, gender identity, sexual orientation, disability, age, military or veteran status, or any other basis protected by applicable local, state, or federal laws or prohibited by Company policy. Observe.AI also strives for a healthy and safe workplace and strictly prohibits harassment of any kind.
We welcome all people. We celebrate diversity of all kinds and are committed to creating an inclusive culture built on a foundation of respect for all individuals. We seek to hire, develop, and retain talented people from all backgrounds. Individuals from non-traditional backgrounds, historically marginalized or underrepresented groups are strongly encouraged to apply.
If you are ambitious, make an impact wherever you go, and you're ready to shape the future of Observe.AI, we encourage you to apply. For more information, visit www.observe.ai.
Ready to apply?
Apply to Observe.AI
Job Title: ML Full stack 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.
Job Description:
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ML Engineer
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Ready to apply?
Apply to Capco
ML Research Engineer (Inference)
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Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. Our novel wafer-scale architecture provides the AI compute power of dozens of GPUs on a single chip, with the programming simplicity of a single device. This approach allows Cerebras to deliver industry-leading training and inference speeds and empowers machine learning users to effortlessly run large-scale ML applications, without the hassle of managing hundreds of GPUs or TPUs.
Cerebras' current customers include top model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
Thanks to the groundbreaking wafer-scale architecture, Cerebras Inference offers the fastest Generative AI inference solution in the world, over 10 times faster than GPU-based hyperscale cloud inference services. This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
About The Role
As a Research Engineer on the Inference ML team at Cerebras Systems, you will adapt today's most advanced language and vision models to run efficiently on our flagship Cerebras architecture. You'll work alongside ML researchers and engineers to design, prototype, validate, and optimize models, gaining end-to-end exposure to cutting-edge inference research on the world's fastest AI accelerator.
You will focus on pushing the frontier of speculative decoding, large-model pruning and compression, sparse attention, and sparsity-driven techniques to deliver low-latency, high-throughput inference at scale.
Responsibilities
- Implement and adapt transformer-based models (NLP and/or vision) to run on Cerebras hardware
- Assist in optimizing models for inference performance (latency, throughput)
- Run experiments, analyze results, and support model improvements
- Help bring up and validate models on the Cerebras system
- Debug and troubleshoot model or system issues with guidance from senior team members
- Support profiling and performance analysis using internal tools
- Collaborate with cross-functional teams (ML, software, hardware) on model integration
Minimum Qualifications
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field
- 1–3 years of experience in software engineering or machine learning in a similar capacity (internships count)
- Experience with Python and at least one ML framework (e.g., PyTorch, Transformers, vLLM or SGLang)
- Understanding of deep learning concepts (e.g., neural networks, transformers)
- Experience with Generative AI and Machine Learning systems
- Strong programming skills in Python and/or C++
Preferred Qualifications
- Experience with speculative decoding, neural network pruning and compression, sparse attention, quantization, sparsity, post-training techniques, and inference-focused evaluations.
- Exposure to large language models or computer vision models
- Experience running experiments or tuning models
- Familiarity with tools like PyTorch, Hugging Face Transformers, or similar
- Basic understanding of performance concepts (e.g., latency, throughput)
- Experience working in Linux environments
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
- Build a breakthrough AI platform beyond the constraints of the GPU.
- Publish and open source their cutting-edge AI research.
- Work on one of the fastest AI supercomputers in the world.
- Enjoy job stability with startup vitality.
- Our simple, non-corporate work culture that respects individual beliefs.
Read our blog: Five Reasons to Join Cerebras in 2026.
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
Ready to apply?
Apply to Cerebras Systems
Kernel Engineer
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Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. Our novel wafer-scale architecture provides the AI compute power of dozens of GPUs on a single chip, with the programming simplicity of a single device. This approach allows Cerebras to deliver industry-leading training and inference speeds and empowers machine learning users to effortlessly run large-scale ML applications, without the hassle of managing hundreds of GPUs or TPUs.
Cerebras' current customers include top model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
Thanks to the groundbreaking wafer-scale architecture, Cerebras Inference offers the fastest Generative AI inference solution in the world, over 10 times faster than GPU-based hyperscale cloud inference services. This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
About The Role
As a Kernel Engineer on our team, you will develop high-performance software solutions at the intersection of hardware and software, developing high-performance software for cutting-edge AI and HPC workloads. Your focus will be on implementing, optimizing, and scaling deep learning operations to fully leverage our custom, massively parallel processor architecture.
You will be part of a world-class team responsible for the design, performance tuning, and validation of foundational ML and HPC kernels. This includes building a library of parallel and distributed algorithms that maximize compute utilization and push the boundaries of training efficiency for state-of-the-art AI models. Your work will be critical to unlocking the full potential of our hardware and accelerating the pace of AI innovation.
Responsibilities
- Develop design specifications for new machine learning and linear algebra kernels and mapping to the Cerebras WSE System using various parallel programming algorithms.
- Develop and debug kernel library of highly optimized low level assembly instruction and C-like domain specific language routines to implement algorithms targeting the Cerebras hardware system.
- Develop and debug high-performance kernel routines in low-level assembly and a custom C-like (CSL) language, implementing algorithms optimized for the Cerebras hardware system.
- Using mathematical models and analysis to measure the software performance and inform design decisions.
- Develop and integrate unit and system testing methodologies to verify correct functionality and performance of kernel libraries.
- Study emerging trends in Machine Learning applications and help evolve Kernel library architecture to address computational challenges of the start-of-the-art Neural Networks.
- Interact with chip and system architects to optimize instruction sets, microarchitecture, and IO of next generation systems.
Skills & Qualifications
- Bachelor’s, Master’s, PhD, or foreign equivalent in Computer Science, Computer Engineering, Mathematics, or a related field.
- Proven experience leading technical teams, including mentoring engineers, setting technical direction, and driving execution.
- Strong understanding of hardware architecture concepts and willingness to dive into new system architectures.
- Proficiency in C++ and Python; experience with low-level systems programming.
- Familiarity with library/API development best practices and performance optimization.
- Excellent debugging skills across complex, layered software stacks.
Preferred Skills & Qualifications
- Experience leading teams in kernel development, performance optimization, or low-level systems programming.
- Strong background in parallel algorithms and distributed memory systems.
- Hands-on experience with accelerators such as GPUs, FPGAs, or other custom hardware.
- Familiarity with machine learning workloads and frameworks like TensorFlow and PyTorch.
- Understanding of HPC kernels and strategies for optimizing them on modern architectures.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
- Build a breakthrough AI platform beyond the constraints of the GPU.
- Publish and open source their cutting-edge AI research.
- Work on one of the fastest AI supercomputers in the world.
- Enjoy job stability with startup vitality.
- Our simple, non-corporate work culture that respects individual beliefs.
Read our blog: Five Reasons to Join Cerebras in 2026.
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
Ready to apply?
Apply to Cerebras Systems
Company Overview
At Skild AI, we are building the world's first general purpose robotic intelligence that is robust and adapts to unseen scenarios without failing. We believe massive scale through data-driven machine learning is the key to unlocking these capabilities for the widespread deployment of robots within society. Our team consists of individuals with varying levels of experience and backgrounds, from new graduates to domain experts. Relevant industry experience is important, but ultimately less so than your demonstrated abilities and attitude. We are looking for passionate individuals who are eager to explore uncharted waters and contribute to our innovative projects.
Position Overview
We are seeking a Computer Vision AI & ML Engineer to design, build, and deploy advanced perception systems for real-world robotics and automation. You will work across the full machine learning lifecycle—model development, data strategy, evaluation, and production integration—to deliver robust, high-performance vision capabilities. This role combines applied research with hands-on engineering and offers the opportunity to influence both architecture and roadmap decisions.
Responsibilities
- Develop and optimize deep learning models for object detection, segmentation, tracking, and 3D scene understanding using multi-modal sensor data.
- Build scalable pipelines for data processing, training, evaluation, and deployment into real-world and real-time systems.
- Design labeling strategies and tooling for automated annotation, QA workflows, dataset management, augmentation, and versioning.
- Implement monitoring and reliability frameworks, including uncertainty estimation, failure detection, and automated performance reporting.
- Conduct proof-of-concept experiments to evaluate new algorithms and perception techniques; translate research insights into practical prototypes.
- Collaborate with robotics, systems, and simulation teams to integrate perception models into production pipelines and improve end-to-end performance.
Preferred Qualifications
- Strong experience with deep learning frameworks (PyTorch, TensorFlow, or JAX).
- Background in computer vision tasks such as detection, segmentation, tracking, or 3D scene understanding.
- Proficiency in Python; familiarity with C++ is a plus.
- Experience building training pipelines, evaluation frameworks, and ML deployment workflows.
- Knowledge of 3D geometry, sensor processing, or multi-sensor fusion (RGB-D, LiDAR, stereo).
- Experience with data annotation tools, dataset management, and augmentation techniques.
- Familiarity with robotics, simulation environments (Isaac Sim, Gazebo, Blender), or real-time systems.
- Understanding of uncertainty modeling, reliability engineering, or ML monitoring/MLOps practices.
Ready to apply?
Apply to Skild AISoftware Engineer, AI Inference
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Company Overview
At Skild AI, we are building the world's first general purpose robotic intelligence that is robust and adapts to unseen scenarios without failing. We believe massive scale through data-driven machine learning is the key to unlocking these capabilities for the widespread deployment of robots within society. Our team consists of individuals with varying levels of experience and backgrounds, from new graduates to domain experts. Relevant industry experience is important, but ultimately less so than your demonstrated abilities and attitude. We are looking for passionate individuals who are eager to explore uncharted waters and contribute to our innovative projects.
Position Overview
We are looking for a Software Engineer to work at the forefront of deploying our cutting-edge AI models, enhancing the performance and capabilities of our embodied systems. You will be responsible for optimizing AI inference processes from lightweight to billion-parameter models, ensuring our robots operate with unmatched efficiency and intelligence in real-world environments. You will work at the intersection of systems and machine learning, directly contributing to making our AI models more powerful and adaptive by ensuring consistent performance in light of variable and perhaps unforeseen compute and hardware constraints.
Responsibilities
- Develop and optimize runtime AI inference pipelines for real-world robotic deployment.
- Build infrastructure, frameworks, and tooling to enable reliable integration of models into robotic systems and informative analysis of production models to drive the direction of architecture choice and deployment system design.
- Formulate specialized optimization solutions for various inference paradigms and scenarios (autoregressive models, denoising models, hierarchical models, state machines, multi-agent systems, cloud-based inference).
- Adapt optimization solutions to various compute, hardware, and networking constraints.
Preferred Qualifications
- BS, MS or higher degree in Computer Science, Robotics, Engineering or a related field, or equivalent practical experience.
- Minimum of 3 years of industry experience.
- Proficiency developing in low-level systems languages (C, C++, Rust, Go), Python and at least one deep learning library such as PyTorch, TensorFlow, JAX, etc.
- Deep understanding and practical experience with low-level systems concepts (multithreading, networking, embedded systems, memory management).
- Experience with CUDA.
- Deep understanding of state-of-the-art machine learning techniques and models.
- Experience optimizing various machine learning architectures.
- Experience with machine learning compilers.
- Experience optimizing model inference for robotic systems deployment.
Ready to apply?
Apply to Skild AIRobotics Engineer, Manipulation
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Company Overview
At Skild AI, we are building the world's first general purpose robotic intelligence that is robust and adapts to unseen scenarios without failing. We believe massive scale through data-driven machine learning is the key to unlocking these capabilities for the widespread deployment of robots within society. Our team consists of individuals with varying levels of experience and backgrounds, from new graduates to domain experts. Relevant industry experience is important, but ultimately less so than your demonstrated abilities and attitude. We are looking for passionate individuals who are eager to explore uncharted waters and contribute to our innovative projects.
Position Overview
We are seeking a versatile Robotics Engineer to develop and implement software solutions for our manipulation systems. The ideal candidate will have experience in controls, perception, and planning. You will be working on deploying state-of-the-art learning-based algorithms on real robot setups, focused on daily manipulation tasks. This role will require close collaboration with researchers and the ML team. The ideal candidate should be comfortable with building high-quality software for robotic manipulation and deploying it on robot hardware.
Responsibilities
- Help design algorithms, models, and techniques for various robotic manipulation tasks.
- Design hardware and software systems for various robotic manipulation tasks.
- Write controllers and perception stacks for real-world robotic deployment.
- Write and maintain production-level C++ and Python code for our robotic manipulation platforms.
- Collaborate with machine learning engineers to deploy state-of-the-art models on our robots.
- Continuously improve and optimize robotic software for performance, reliability, and scalability.
Preferred Qualifications
- BS, MS or higher degree in Computer Science, Robotics, Engineering or a related field, or equivalent practical experience.
- Experience in designing robotic manipulation systems and deploying software on real robots.
- Experience with writing controllers and knowledge of robotics (e.g., kinematics, dynamics, control, motion planning, SLAM).
- Proficiency in Python and at least one deep learning library such as PyTorch, TensorFlow, JAX, etc.
- Systems-level understanding of the various software modules and their interfaces in a robotic application (ROS/ROS2, simulators, etc.).
- Publications at top-tier ML, robotics or CV conferences (e.g., NeurIPS, ICML, ICLR, CoRL, RSS, ICRA, CVPR, ECCV, ICCV).
- Experience with designing custom robot hardware solutions.
- Proficiency with various robot learning techniques (RL, imitation learning, etc.).
- Experience working with modern computer vision algorithms, sensors (LiDAR, camera, radar, etc.), 3D (meshes, point clouds, etc.), segmentation, tracking, object detection.
Ready to apply?
Apply to Skild AISoftware Engineer, AI Training and Infrastructure
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Company Overview
At Skild AI, we are building the world's first general purpose robotic intelligence that is robust and adapts to unseen scenarios without failing. We believe massive scale through data-driven machine learning is the key to unlocking these capabilities for the widespread deployment of robots within society. Our team consists of individuals with varying levels of experience and backgrounds, from new graduates to domain experts. Relevant industry experience is important, but ultimately less so than your demonstrated abilities and attitude. We are looking for passionate individuals who are eager to explore uncharted waters and contribute to our innovative projects.
Position Overview
We are looking for a Software Engineer to work at the forefront of developing and optimizing the software infrastructure and tools necessary for training cutting-edge AI models. You will focus on building robust, scalable, and efficient training pipelines and frameworks that support the entire machine learning lifecycle, from data preparation to model deployment. You will collaborate with researchers and machine learning engineers to ensure seamless integration and operation of training systems, pushing the boundaries of what AI can achieve in real-world robotics applications. You will explore new ways to efficiently make use of many types of data in our training pipeline.
Responsibilities
- Develop and maintain robust, scalable, and distributed training pipelines (data preprocessing, training orchestration, and model evaluation) and frameworks for large-scale AI models.
- Optimize training processes for performance and resource utilization, ensuring scalability and reliability.
- Collaborate with researchers and machine learning engineers to integrate state-of-the-art algorithms and techniques into training pipelines.
- Monitor and analyze training, identifying bottlenecks and proposing solutions to improve efficiency and performance.
- Ensure the robustness and reliability of the training infrastructure, including automated testing and continuous integration.
Preferred Qualifications
- BS, MS or higher degree in Computer Science, Robotics, Engineering or a related field, or equivalent practical experience.
- Minimum of 3 years of industry experience.
- Proficiency in Python, C++, or similar and at least one deep learning library such as PyTorch, TensorFlow, JAX, etc.
- Strong background in distributed computing, parallel processing techniques, handling large-scale datasets and data preprocessing.
- Deep understanding of state-of-the-art machine learning techniques and models.
- Experience with cloud-based training environments (AWS, Google Cloud, Azure).
- Experience in developing and maintaining software tooling and infrastructure for machine learning.
- Deep understanding and practical experience with software engineering principles, including algorithms, data structures, and system design.
- Experience with continuous integration and automated testing frameworks.
Ready to apply?
Apply to Skild AIHeadquartered in Los Altos, CA. Backed by SAIGroup.
Learn more about JazzX AI:
Website: https://jazzx.ai
LinkedIn: https://www.linkedin.com/company/jazzx-ai
Learn more about SAIGroup:
Website: https://saigroup.ai
Senior Staff Engineer
As a Senior Staff Engineer at JazzX AI, you will operate as a strategic technical leader—driving platform architecture, guiding critical projects, and influencing product direction. You will serve as a hands-on contributor, provide technical mentorship across teams, and partner with senior stakeholders to ensure our solutions are innovative, robust, and aligned with the company’s long-term vision. You will also be instrumental in fostering a high-performance engineering culture that emphasizes collaboration, excellence, and continuous improvement.
Key Responsibilities
Technical Leadership & Architecture
- Define and evolve JazzX.ai’s technical strategy, ensuring our AI-driven systems can scale and adapt to future challenges.
- Own the end-to-end architecture for key platform components, ensuring high levels of reliability, security, and performance.
- Evaluate emerging technologies, tools, and frameworks, making data-driven recommendations that influence company-wide engineering decisions.
Project Execution & Cross-Functional Collaboration
- Lead complex, high-impact engineering initiatives that require coordination across multiple product and infrastructure teams.
- Collaborate with Product Management, AI research engineering, , and UX to scope technical requirements and deliver solutions that align with business objectives.
- Serve as a trusted advisor to senior stakeholders, clearly communicating technical roadmaps, trade-offs, and risks.
Mentorship & Team Development
- Guide and mentor engineers at all levels, from early-career to senior staff, providing technical direction and career development support.
- Champion best practices in code quality, architecture reviews, testing, and documentation.
- Foster an inclusive and innovative engineering culture, encouraging knowledge-sharing and continuous learning.
Innovation & AI Integration
- Partner with the AI research engineering team team to design and implement modern AI frameworks and capabilities as production services in the platform
- Drive the exploration and adoption of state-of-the-art AI/ML technologies to keep JazzX.ai ahead of industry trends.
- Identify strategic opportunities where AI can deliver enhanced functionality or novel capabilities for our platform.
Operational Excellence
- Define and enforce SLAs for mission-critical services, ensuring minimal downtime and fast recovery.
- Champion DevOps best practices around CI/CD, cloud infrastructure, observability, and security.
- Collaborate with Site Reliability Engineers (SREs) and Security teams to optimize performance and maintain compliance with industry standards.
Qualifications
Educational Background
- Bachelor’s or Master’s in Computer Science, Engineering, or a related field; or equivalent experience.
Experience & Technical Expertise
- 10–12+ years of professional software engineering experience, with at least 5 years in technical leadership roles (Principal, Staff, or equivalent).
- Proven track record leading complex, large-scale projects across distributed systems, backend architecture, or cloud platforms.
- Deep expertise in at least one or more programming languages (e.g., Python, Java, Javascript, Go, C++), with a willingness to learn new technologies.
- Strong understanding of microservices, event-driven architectures, and container orchestration tools (Kubernetes, Docker).
- Experience with large-scale data processing, streaming platforms (e.g., Kafka), and databases (both SQL and NoSQL).
- Familiarity with AI/ML frameworks (TensorFlow, PyTorch) and operationalizing machine learning solutions is a plus.
AI/ML Experience:
- Demonstrated experience in designing, building, deploying, and managing Machine Learning (ML) and Artificial Intelligence (AI) platforms and services. Hands on experience with MLOps practices, frameworks (TensorFlow, PyTorch), and tools.
- Experience building platforms and applications with modern LLMs and AI agent frameworks like LangChain, LlamaIndex , AutoGen etc. is a strong plus
Leadership & Soft Skills
- Exceptional communication and presentation skills, with the ability to influence technical and non-technical stakeholders at executive levels.
- Proven ability to mentor, coach, and inspire engineers, build high-performing teams and a culture of engineering excellence.
- Experience navigating ambiguous requirements and delivering results in a fast-paced, startup environment.
- Demonstrated thought leadership in architectural design, code quality, and technical strategy.
Why Join JazzX AI:
What draws people to JazzX AI is the opportunity to build something truly foundational.
We are at the beginning of a new era — one where enterprise systems will no longer be static tools, but dynamic collaborators that learn, reason, and evolve alongside the people who use them. At JazzX AI, you’ll help build a platform that redefines how work happens in the AGI era.
JazzX AI brings together vision, deep technology, and purpose. This is not about experimenting with AI features; it’s about turning the promise of AGI into practical, auditable, and human-aligned systems that enterprises can trust and rely on at scale. The work here directly impacts productivity, efficiency, and decision-making in complex, real-world environments.
If you’re motivated by building systems that matter — systems that combine intelligence with responsibility — JazzX AI offers the chance to do that work at a deeper level, with real ownership and lasting impact.
Ready to apply?
Apply to JazzX AIHeadquartered in Los Altos, CA. Backed by SAIGroup.
Learn more about JazzX AI:
Website: https://jazzx.ai
LinkedIn: https://www.linkedin.com/company/jazzx-ai
Learn more about SAIGroup:
Website: https://saigroup.ai
Staff Software Development Engineer
As a Staff Software Development Engineer at JazzX AI, you'll define the technical vision for our enterprise AI platform, mentor senior engineers, and oversee the design, development, and deployment of critical AI, software and infra services and components. You'll be responsible for ensuring the platform's scalability, reliability, security and observability.
What You Will Do
Design and Architect Scalable Solutions:
- Lead the design and development of high-performance, scalable services and components for our enterprise AI platform using a cloud-first, cloud-agnostic approach with world class AI capabilities, scalability, security, privacy and operability.
- Champion a cloud-first, cloud-agnostic approach to ensure platform versatility, scalability, and future-proof architecture.
- Champion innovative AI and software design patterns and best practices to ensure code maintainability, reusability, and testability.
- Contribute to the platform's technical direction by staying up to date on emerging AI technologies, cloud design patterns and user experience methodologies.
Collaborative Innovation:
- Foster a collaborative environment by working closely with cross-functional teams (AI/research engineers, software engineers, architects, product managers, and designers) to translate complex platform and product requirements into elegant, scalable, and modular AI, software and infrastructure components.
- Foster a collaborative and inclusive environment by effectively communicating technical concepts and design decisions across diverse audiences.
- Provide mentorship and guidance to junior engineers, fostering their growth and development.
Driving Operational Excellence:
- Oversee the seamless integration of components into the platform, ensuring efficient operation, reliability, and a dependable user experience for both customers and partners.
- Champion DevOps and AIOps best practices for AI services, maintainability, performance optimization, and observability.
Requirements
- Minimum 8+ years of experience designing, building, and operating cloud-native applications at scale. Expertise in container orchestration frameworks like Kubernetes and containerization technologies like Docker. Expertise in AI/ML/data capabilities, platforms, frameworks and tools.
- Proven track record deploying and managing cloud environments using Infrastructure as Code (IaC) tools like Terraform, Ansible, or CloudFormation.
- Experience in designing and implementing highly available, scalable, and fault-tolerant systems.
Development Lifecycle:
- End-to-end ownership of the entire software development lifecycle (SDLC) for complex enterprise platforms and products. This includes experience in design, prototyping, development (including unit, integration, and end-to-end testing), deployment, and ongoing operations.
Technical Skills:
- Mastery of essential software development principles with a focus on clean code, design patterns, and best practices.
- In-depth expertise in at least two of the following programming languages: Python, Java, JavaScript, Golang, or C++.
- Solid understanding of distributed systems concepts and experience with distributed tracing tools.
AI/ML Experience:
- Demonstrated experience in building, deploying, and managing Machine Learning (ML) and Artificial Intelligence (AI) platforms and services. Familiarity with MLOps practices, frameworks (TensorFlow, PyTorch), and tools is a plus
- Familiarity with modern LLMs and AI agent frameworks like LangChain, LlamaIndex , AutoGen etc. is a strong plus
Why Join JazzX AI:
What draws people to JazzX AI is the opportunity to build something truly foundational.
We are at the beginning of a new era — one where enterprise systems will no longer be static tools, but dynamic collaborators that learn, reason, and evolve alongside the people who use them. At JazzX AI, you’ll help build a platform that redefines how work happens in the AGI era.
JazzX AI brings together vision, deep technology, and purpose. This is not about experimenting with AI features; it’s about turning the promise of AGI into practical, auditable, and human-aligned systems that enterprises can trust and rely on at scale. The work here directly impacts productivity, efficiency, and decision-making in complex, real-world environments.
If you’re motivated by building systems that matter — systems that combine intelligence with responsibility — JazzX AI offers the chance to do that work at a deeper level, with real ownership and lasting impact.
Ready to apply?
Apply to JazzX AITeamwork 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 role
We seek an outstanding, creative, and passionate Machine Learning Platform Engineer to join Roku's Recommendation team. In this role, you will design, build, and scale robust distributed systems that power the next generation of personalized content recommendations for millions of Roku users. You will focus on developing end-to-end machine learning platforms and infrastructure, ensuring seamless deployment, monitoring, and optimization of algorithms and operational workflows that deliver unique experiences at scale.
What You'll Be Doing
- Design, build, and maintain scalable platform services: feature store, real-time inference services, vector DBs etc., that serve millions of transactions per second.
- Run and monitor online AB tests via robust platform services, analyzing platform metrics and business KPIs to optimize recommendation system performance.
- Collaborate closely with US-based engineering and cross-functional teams to translate business requirements into modular platform components and APIs.
- Enhance and evolve the ML platform ecosystem to support high developer velocity, system scalability, and adaptability to future business needs.
- Contribute to onboarding, training, and mentoring new team members on emerging platform engineering best practices and technologies.
We’re excited if you have - 5+ years of experience building software solutions to concrete problems
- Strong CS fundamentals. Should be able to write an algorithm with ease
- You are fluent with one of high-level programming languages like Java, Scala, Kotlin or Python
- We’d love to see that you’ve worked with big data systems (Spark, Kafka, Flink, S3, AirFlow)
- Familiar with model ML framework and tools: Ray, PyTorch, HuggingFace, AWS Sagemaker
- AI literacy and curiosity.You have either tried Gen AI in your previous work or outside of work or are curious about Gen AI and have explored it.
- MS in Computer Science or related field
#LI-NK1
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.
Ready to apply?
Apply to Roku
AI Engineer - FDE (Forward Deployed Engineer)
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CSQ326R35
Mission
The AI Forward Deployed Engineering (AI FDE) team is a highly specialized customer-facing AI team at Databricks. We deliver professional services engagements to help our customers build and productionize first-of-its-kind AI applications. We work cross-functionally to shape long-term strategic priorities and initiatives alongside engineering, product, and developer relations, as well as support internal subject matter expert (SME) teams. We view our team as an ensemble: we look for individuals with strong, unique specializations to improve the overall strength of the team. This team is the right fit for you if you love working with customers, teammates, and fueling your curiosity for the latest trends in GenAI, LLMOps, and ML more broadly. This role can be remote.
The impact you will have:
- Develop cutting-edge GenAI solutions, incorporating the latest techniques from our Mosaic AI research to solve customer problems
- Own production rollouts of consumer and internally facing GenAI applications
- Serve as a trusted technical advisor to customers across a variety of domains
- Present at conferences such as Data + AI Summit, recognized as a thought leader internally and externally
- Collaborate cross-functionally with the product and engineering teams to influence priorities and shape the product roadmap
What we look for:
- Experience building GenAI applications, including RAG, multi-agent systems, Text2SQL, fine-tuning, etc., with tools such as HuggingFace, LangChain, and DSPy
- Minimum of 5+ years of relevant experience as a Data Scientist preferably working in a consulting role
- Expertise in deploying production-grade GenAI applications, including evaluation and optimizations
- Extensive years of hands-on industry data science experience, leveraging common machine learning and data science tools, i.e. pandas, scikit-learn, PyTorch, etc.
- Experience building production-grade machine learning deployments on AWS, Azure, or GCP
- Graduate degree in a quantitative discipline (Computer Science, Engineering, Statistics, Operations Research, etc.) or equivalent practical experience
- Experience communicating and/or teaching technical concepts to non-technical and technical audiences alike
- Passion for collaboration, life-long learning, and driving business value through AI
- [Preferred] Experience using the Databricks Intelligence Platform and Apache Spark™ to process large-scale distributed datasets
About Databricks
Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook.
Benefits
At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here.
Our Commitment to Diversity and Inclusion
At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.
Compliance
If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.
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Apply to Databricks
Senior Data Scientist - Ad Optimization, India
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At Branch, we power every touchpoint with links that work and insights that prove it. From click to conversion, we make growth measurable. Our unparalleled attribution, backed by AI-enhanced linking, is trusted to deliver seamless experiences that increase ROI, decrease wasted spend, and eliminate siloed attribution.
We bring the same rigor to how we build our team, by empowering our people to move fast, own outcomes, and build something that matters. We take pride in making meaningful investments in our team’s health, wealth, and growth so individuals can thrive as we scale. Our culture values smart, humble, and collaborative teammates who take accountability and drive results in an environment where their work truly moves the business forward.
We are innovative, scaling with purpose, and led by seasoned leaders who know how to build enduring companies. Trusted by brands like Instacart, Western Union, NBCUniversal, ZocDoc, and Sephora, we’re big enough to matter, small enough for you to make a real impact. If you’re excited by the grit of building, rapid learning, and shaping the future of customer growth, you’ll find your place here.
We are seeking an experienced and highly skilled Senior Data Scientist to lead our efforts in optimizing ad display on native Android surfaces. In this role, you will design and implement data-driven strategies to maximize ad effectiveness, user engagement, and revenue. You will collaborate closely with product managers, engineers, and cross-functional teams to drive innovation, improve ad relevance, and ensure a seamless user experience.
As a Senior Data Scientist, you’ll get to:
- Develop and refine data-driven ad optimization strategies tailored to native Android environments, focusing on user engagement, personalization, and revenue uplift.
- Design, implement, and improve predictive models for ad targeting, recommendation, and bidding strategies using cutting-edge machine learning and statistical techniques.
- Lead the design and analysis of experiments to test ad placements, formats, and targeting methods. Use data from A/B tests and multivariate testing to validate hypotheses and inform decisions.
- Analyze user behavior patterns to understand engagement and dropout points, leveraging insights to optimize ad positioning, timing, and relevance.
- Partner with product managers, engineers, designers, and marketing teams to align ad strategies with business objectives and user experience goals. Communicate insights and recommendations effectively to both technical and non-technical stakeholders.
- Ensure the scalability of ad models across a wide range of Android devices and varying network conditions. Work closely with engineering teams to deploy and monitor models in a production environment.
- Provide mentorship and guidance to junior data scientists, fostering a collaborative and innovative team environment. Lead by example in developing high-quality, scalable solutions for complex ad optimization challenges.
You’ll be a good fit if you have:
- PhD (preferred) or Master's Degree (required) in Computer Science, Data Science, Statistics, Machine Learning, or a related field.
- 6+ years of experience in data science or machine learning, with a strong focus on ad technology or user experience optimization.
- Demonstrable experience in working with ad serving, ad tech stacks, and optimization techniques, especially within Android or mobile ecosystems.
- Expertise in machine learning frameworks (TensorFlow, PyTorch, or similar).
- Advanced proficiency in Python, or Kotlin.
- Experience with data processing and pipeline tools (e.g., Spark, Hadoop, Airflow).
- Deep understanding of A/B testing, causal inference, and other experimentation methods.
- Familiarity with ad tech, programmatic advertising, and user behavior metrics, particularly in the context of mobile and Android platforms.
- Excellent analytical, problem-solving, and communication skills. Proven ability to articulate complex data science concepts to stakeholders across different domains.
Nice to have:
- Previous experience optimizing ad displays on native mobile or Android surfaces.
- Familiarity with the Android SDK and understanding of native Android UI/UX design principles.
- Knowledge of reinforcement learning, multi-armed bandit models, and contextual targeting techniques.
This role is based at our Bengaluru, India office and follows a Hybrid schedule that will be aligned with our Return to Office guidelines.
The salary range provided represents base compensation and does not include potential equity, which is available for qualifying positions. At Branch, we are committed to the well-being of our team by offering a comprehensive benefits package. From health and wellness programs to paid time off and retirement planning options, we provide a range of benefits for qualified employees. For detailed information on the benefits specific to your position, please consult with your recruiter.
Branch is an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.
If you think you'd be a good fit for this role, we'd love for you to apply! At Branch, we strive to create an inclusive culture that encourages people from all walks of life to bring their unique, diverse perspectives to work. We aim every day to build an environment that empowers us all to do the best work of our careers, and we can't wait to show you what we have to offer!
A little bit about us:
Branch is the leading provider of engagement and performance mobile SaaS solutions for growth-focused teams, trusted to maximize the value of their evolving digital strategies. The Branch platform provides a seamless experience across paid and organic, on all channels and platforms, online and offline, to eliminate friction and drive valuable action at the moments of highest intent. With Branch, businesses gain accurate mobile measurement and insights into user interactions, enabling them to drive conversions, engagement, and more intelligent marketing spend.
Branch is an award-winning employer headquartered in Mountain View, CA. World-class brands like Instacart, Western Union, NBCUniversal, Zocdoc and Sephora acquire users, retain customers and drive more conversions with Branch.
Candidate Privacy Information:
For more information on the data that Branch will collect through your application, and how we use, share, delete, and retain that information as part of our recruitment and employment efforts, please see our HR Privacy Policy.
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Apply to Branch Metrics
About Nanonets
Nanonets has a vision to help computers see the world starting with reading and understanding documents.Machine Learning (ML) is no longer a futuristic concept—it's a present-day powerhouse transforming the business landscape. Nanonets is at the forefront of this transformation, offering innovative ML solutions designed to make document related processes faster than ever before.
From automating data extraction processes to enhancing reconciliation, our solutions are designed to revolutionize workflows, optimize operations, and unlock untapped potential for our clients. Our client footprint spans across brands such as Toyota, Boston Scientific, Bill.com and Entergy to name a few enabling businesses across a myriad of industries to unlock the potential of their visual and textual data
We recently announced a series B round of $29 million in funding by Accel and are backed by the likes of existing investors including Elevation Capital & YCombinator. This infusion of capital underscores our commitment to driving innovation and expanding our reach in delivering cutting-edge AI solutions to businesses worldwide.
We’re on a mission to hire the very best and are committed to creating exceptional employee experiences where everyone is respected and has access to equal opportunity.
About the Role
As a senior fullstack engineer, you should be comfortable with both backend (Preferably Golang) and frontend (Preferably React). You will be primarily working on architecting and shipping new backend features like new integrations, enabling more machine learning API’s, building complex workflows & various growth hacking efforts. You will also work on optimizing response times, building features that will scale to 100’s of millions of documents we process every month.
What we expect from you
- Agility in shipping features
- Good at code design and architecture
- Great communication
- Backend experience - Preferably golang, python
- Databases - Understanding of data modeling for Nosql preferably cassandra.
- Strong fundamentals in OOP design patterns.
- Basic understanding of Devops.
- Curiosity and Willingness to learn new things while solving a challenging problem.
- Learning and incorporating best practices in software development, security and design/architecture.
What We're Looking For:
- B.E/B.Tech preferable from a Tier 1 college
- 3-8 yrs in software development with a strong foundation in software architecture and design as well one of frontend and backend development
- Proficiency in programming and development technologies.
- Strong familiarity with DevOps best practices and tools.
- Innovative mindset and a passion for driving engineering excellence.
Some of the interesting features we have shipped in backend
- Compile python code into C which could be imported into golang and then shipped as binary for on premise systems
- Autoscale GPU dependent services with kubernetes with a custom metric
- Displaying machine learning metrics in simplified ways to end users so they can act based on those metrics
- Building large number and variety of integrations with relatively generic interface like salesforce, quickbooks, RPA's, external databases
- Process large number of files in highly distributed manner in golang
- Intelligent lookups leveraging vector databases with data synced from ERP Systems
Some of the interesting things we have shipped in frontend -
- Ability for users to annotate documents so AI can learn which fields to extract.
- Displaying machine learning metrics in simplified ways to end users so they can act based on those metrics
- Letting users build complex visual workflows around our API in our product.
- Let users visualize complex ML metrics in a very simple and intuitive way
Our Tech Stack
- Databases
- Cassandra DB
- Postgres/MySQL
- Backend
- Golang for API and other microservices
- Python for Machine learning (Tensorflow, Pytorch)
- Frontend
- React, Typescript
- Mobx
- Cloud Providers
- AWS
- GCP for ML heavy workload
- Monitoring/Alerting
- ELK for logging
- Prometheus for Monitoring
- Graphana for dashboards
- Orchestration
- Kubernetes
- DevOps
- Jenkins for CI/CD
Ready to apply?
Apply to Nanonets
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.
Tekion seeks an exceptionally talented and seasoned Staff / Lead Applied Scientist to architect the future of our AI-driven solutions. The incumbent will assume a pivotal role in our organization, providing the strategic and technical stewardship necessary to translate cutting-edge research into tangible business value. The ideal candidate is a first-principles thinker, adept at navigating ambiguity, and possesses the intellectual curiosity to formulate and solve complex, unstructured problems. This is seminal opportunity to influence the trajectory of our AI strategy and deliver transformative solutions at an enterprise scale.
Key Responsibilities
- Strategic Direction: Architect and execute the strategic vision for applied AI and Machine Learning within Tekion, ensuring rigorous alignment with overarching business objectives and industry challenges.
- Innovation & Research Leadership: Steer the R&D roadmap by identifying and capitalizing on emergent technological opportunities. Drive innovation through the ideation and implementation of novel, scientifically-grounded solutions.
- Stakeholder Alignment: Serve as the principal technical liaison between the R&D organization and executive stakeholders, ensuring technical strategies are congruent with business imperatives.
- Cross-Functional Execution: Lead collaborations with product, engineering, and business units to define, develop, and integrate sophisticated machine learning systems into core products and services.
- Scientific Contribution: Contribute to the broader scientific community through publications in premier academic conferences and journals, enhancing Tekion's position as a center of innovation.
- Mentorship & Talent Development: Mentor and cultivate a culture of scientific rigor and innovation among applied scientists, guiding project execution and fostering professional growth.
- Impact Quantification: Establish robust frameworks for model evaluation and performance measurement. Quantify and articulate the business impact of machine learning initiatives to executive leadership.
- Governance & Best Practices: Institute and govern best practices for the entire machine learning lifecycle, including model development, validation, deployment, and monitoring, while championing ethical and responsible AI
Core Competencies & Technical Expertise
The successful candidate will demonstrate mastery in the following areas:
- Foundational Expertise: Deep, theoretical and practical expertise in Machine Learning, Deep Learning, Causal Inference, and Explainable AI.
- Statistical Rigor: Advanced proficiency in applied probability and statistics to derive and validate insights from complex, high-dimensional data.
Deep Learning:
- Expert-level proficiency with frameworks such as TensorFlow, Keras, and PyTorch.
- Extensive experience implementing advanced neural network architectures.
- Practical application of Computer Vision (e.g., OpenCV) and Natural Language Processing (e.g.,spaCy) methodologies.
- Large Language Models (LLMs): Demonstrated experience with Large Language Models, including advanced prompt engineering, fine-tuning, and deployment for specific business applications.
Technical Proficiencies:
- Advanced programming skills in Python and mastery of SQL. Familiarity with distributed computing frameworks (e.g., Spark) is advantageous.
- Proficiency with cloud computing platforms (GCP, Azure, AWS).
- Expertise in experimental design (A/B testing, causal inference).
- Proficient in version control systems (Git).
Required Qualifications
- An advanced degree (Ph.D. or M.S. preferred) in a quantitative discipline such as Computer Science, Statistics, Operations Research, Physics, or a related field.
- A minimum of 7 - 9 years of post-academic experience in applied science or quantitative research roles, with a demonstrable history of translating complex models into tangible business value.
- A distinguished track record of solving difficult, business-critical problems using a scientific, data-driven approach.
- Proven experience in programming, data manipulation, and building models in a business context.
- Sophisticated data visualization and presentation skills, with the ability to distill complex analytical results into clear, actionable insights for diverse audiences.
Ideal Candidate Profile
- A profound intellectual curiosity and a systematic, first-principles approach to problem-solving.
- Domain expertise in the automotive industry or related fields such as finance or enterprise SaaS is highly desirable.
- Experience in specialized areas such as Recommendation Engines or advanced NLP is preferred.
- Exceptional communication and presentation capabilities, with a proven ability to distill complex technical concepts for executive-level audiences.
- A demonstrated ability to work collaboratively and effectively lead initiatives across multi-disciplinary teams.
- A commitment to continuous personal and team development within a collaborative, high-performance culture.
Perks and Benefits
- Competitive compensation
- Generous stock options
- Medical Insurance coverage
- Work with some of the brightest minds from Silicon Valley’s most dominant and successful companies
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.
Ready to apply?
Apply to Tekion
Data Science- Manager
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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.
|
2,200+
Customers
|
10 of Top 12
CPG Companies
|
900+
Retailers Connected
|
$200M+
Raised
|
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.
Technical Expertise
- Strong background in machine learning, deep learning, and NLP, with proven experience in training and fine-tuning large-scale models (LLMs, transformers, diffusion models, etc.).
- Hands-on expertise with Parameter-Efficient Fine-Tuning (PEFT) approaches such as LoRA, prefix tuning, adapters, and quantization-aware training.
- Proficiency in PyTorch, TensorFlow, Hugging Face ecosystem and good to have distributed training frameworks (e.g., DeepSpeed, PyTorch Lightning, Ray).
- Basic understanding of MLOps best practices, including experiment tracking, model versioning, CI/CD for ML pipelines, and deployment in production environments.
- Experience working with large datasets, feature engineering, and data pipelines, leveraging tools such as Spark, Databricks, or cloud-native ML services (AWS Sagemaker, GCP Vertex AI or Azure ML).
- Knowledge of GPU/TPU optimization, mixed precision training, and scaling ML workloads on cloud or HPC environments.
- Applied Problem-Solving
Mandatory skill -
- Demonstrated success in adapting foundation models to domain-specific applications through fine-tuning or transfer learning.Mandatory skill -
- Strong ability to design, evaluate, and improve models using robust validation strategies, bias/fairness checks, and performance optimization techniques.
- Experience in working on applied AI problems across NLP, computer vision, or multimodal systems or any other domain.
Leadership & Collaboration
- Proven ability to lead and mentor a team of applied scientists and ML engineers, providing technical guidance and fostering innovation.
- Strong cross-functional collaboration skills to work with product, engineering, and business stakeholders to deliver impactful AI solutions.
- Ability to translate cutting-edge research into practical, scalable solutions that meet real-world business needs.
Other
- Excellent communication and presentation skills to articulate complex ML concepts to both technical and non-technical audiences.
- Continuous learner with awareness of emerging trends in generative AI, foundation models, and efficient ML techniques.
Education & Experience
- Master’s or Ph.D. in Computer Science, Machine Learning, Data Science, Statistics, or a related field.
- 7+ years of hands-on experience in applied machine learning and data science, with at least 2+ years in a leadership or managerial role.
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.
Ready to apply?
Apply to CommerceIQLead Data Scientist
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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.
|
2,200+
Customers
|
10 of Top 12
CPG Companies
|
900+
Retailers Connected
|
$200M+
Raised
|
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.
Technical Expertise
- Strong background in machine learning, deep learning, and NLP, with proven experience in training and fine-tuning large-scale models (LLMs, transformers, diffusion models, etc.).
- Hands-on expertise with Parameter-Efficient Fine-Tuning (PEFT) approaches such as LoRA, prefix tuning, adapters, and quantization-aware training.
- Proficiency in PyTorch, TensorFlow, Hugging Face ecosystem and good to have distributed training frameworks (e.g., DeepSpeed, PyTorch Lightning, Ray).
- Basic understanding of MLOps best practices, including experiment tracking, model versioning, CI/CD for ML pipelines, and deployment in production environments.
- Experience working with large datasets, feature engineering, and data pipelines, leveraging tools such as Spark, Databricks, or cloud-native ML services (AWS Sagemaker, GCP Vertex AI or Azure ML).
- Knowledge of GPU/TPU optimization, mixed precision training, and scaling ML workloads on cloud or HPC environments.
- Applied Problem-Solving
Mandatory skill -
- Demonstrated success in adapting foundation models to domain-specific applications through fine-tuning or transfer learning.Mandatory skill -
- Strong ability to design, evaluate, and improve models using robust validation strategies, bias/fairness checks, and performance optimization techniques.
- Experience in working on applied AI problems across NLP, computer vision, or multimodal systems or any other domain.
Leadership & Collaboration
- Proven ability to lead and mentor a team of applied scientists and ML engineers, providing technical guidance and fostering innovation.
- Strong cross-functional collaboration skills to work with product, engineering, and business stakeholders to deliver impactful AI solutions.
- Ability to translate cutting-edge research into practical, scalable solutions that meet real-world business needs.
Other
- Excellent communication and presentation skills to articulate complex ML concepts to both technical and non-technical audiences.
- Continuous learner with awareness of emerging trends in generative AI, foundation models, and efficient ML techniques.
Education & Experience
- Master’s or Ph.D. in Computer Science, Machine Learning, Data Science, Statistics, or a related field.
- 5+ years of hands-on experience in applied machine learning and data science.
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.
Ready to apply?
Apply to CommerceIQData Scientist II
Share this job
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.
|
2,200+
Customers
|
10 of Top 12
CPG Companies
|
900+
Retailers Connected
|
$200M+
Raised
|
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.
Technical Expertise:
- Strong background in machine learning, deep learning, and NLP, with proven experience in training and fine-tuning large-scale models (LLMs, transformers, diffusion models, etc.).
- Hands-on expertise with Parameter-Efficient Fine-Tuning (PEFT) approaches such as LoRA, prefix tuning, adapters, and quantization-aware training.
- Proficiency in PyTorch, TensorFlow, Hugging Face ecosystem and good to have distributed training frameworks (e.g., DeepSpeed, PyTorch Lightning, Ray).
- Basic understanding of MLOps best practices, including experiment tracking, model versioning, CI/CD for ML pipelines, and deployment in production environments.
- Experience working with large datasets, feature engineering, and data pipelines, leveraging tools such as Spark, Databricks, or cloud-native ML services (AWS Sagemaker, GCP Vertex AI or Azure ML).
- Knowledge of GPU/TPU optimization, mixed precision training, and scaling ML workloads on cloud or HPC environments.
Applied Problem-Solving:
- Mandatory skill - Demonstrated success in adapting foundation models to domain-specific applications through fine-tuning or transfer learning.
- Mandatory skill - Strong ability to design, evaluate, and improve models using robust validation strategies, bias/fairness checks, and performance optimization techniques.
- Experience in working on applied AI problems across NLP, computer vision, or multimodal systems or any other domain.
Leadership & Collaboration:
- (Preferred) Proven ability to lead and mentor a junior applied scientists and ML engineers, providing technical guidance and fostering innovation.
- Strong cross-functional collaboration skills to work with product, engineering, and business stakeholders to deliver impactful AI solutions.
- Ability to translate cutting-edge research into practical, scalable solutions that meet real-world business needs.
Education & Experience:
- 3+ years of hands-on experience in applied machine learning and data science with Master’s or Ph.D. in Computer Science, Machine Learning, Data Science, Statistics, or a related field or appropriate experience.
- Excellent communication and presentation skills to articulate complex ML concepts to both technical and non-technical audiences.
- Continuous learner with awareness of emerging trends in generative AI, foundation models, and efficient ML techniques.
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.
Ready to apply?
Apply to CommerceIQ
What you will do:
The role requires you to be part of the team that helps productize the SW stack for our AI compute engine. As part of the software team, you will be responsible for the development, enhancement, and maintenance of software kernels for next-generation AI hardware. You possess experience building software kernels for HW architectures. You possess a very strong understanding of various hardware architectures and how to map algorithms to the architecture. You understand how to map computational graphs generated by AI frameworks to the underlying architecture. You have had past experience working across all aspects of the full stack toolchain and understand the nuances of what it takes to optimize and trade off various aspects of hardware-software co-design. You are able to build and scale software deliverables in a tight development window. You will work with a team of compiler experts to build out the compiler infrastructure, working closely with other software (ML, systems) and hardware (mixed signal, DSP, CPU) experts in the company.
What you will bring:
Minimum:
MS or PhD in Computer Engineering, Math, Physics, or related degree with 10+ years of industry experience Strong grasp of computer architecture, data structures, system software, and machine learning fundamentals Proficient in C/C++ and Python development in Linux environment and using standard development tools Experience implementing algorithms in high-level languages such as C/C++ and Python Experience implementing algorithms for specialized hardware such as FPGAs, DSPs, GPUs, AI accelerators using libraries such as CuDA etc. Experience in implementing operators commonly used in ML workloads—GEMMs, Convolutions, BLAS, SIMD operators for operations like softmax, layer normalization, pooling, etc. Experience with development for embedded SIMD vector processors such as Tensilica. Self-motivated team player with a strong sense of ownership and leadership
Preferred:
Prior startup, small team, or incubation experience.
Experience with ML frameworks such as TensorFlow and/or PyTorch.
Experience working with ML compilers and algorithms, such as MLIR, LLVM, TVM, Glow, etc.
Experience with a deep learning framework (such as PyTorch or TensorFlow) and ML models for CV, NLP, or recommendation.
Work experience at a cloud provider or AI comp.
Ready to apply?
Apply to PhizenixLocation: Hybrid, working onsite at our Bengaluru, India offices 3-5 days per week.
What you will do:
The role requires you to be part of the team that helps productize the SW stack for our AI compute engine. As part of the software team, you will be responsible for the development,
enhancement, and maintenance of software kernels for next-generation AI hardware. You possess experience building software kernels for HW architectures. You possess a very strong
understanding of various hardware architectures and how to map algorithms to the architecture. You understand how to map computational graphs generated by AI frameworks to the
underlying architecture. You have had past experience working across all aspects of the full stack toolchain and understand the nuances of what it takes to optimize and trade off various
aspects of hardware-software co-design. You can build and scale software deliverables in a tight development window. You will work with a team of compiler experts to build out the
compiler infrastructure, working closely with other software (ML, systems) and hardware (mixed signal, DSP, CPU) experts in the company.
What you will bring:
Minimum:
MS in computer engineering, math, physics, or a related degree with 5+ years of industry experience or PhD in computer engineering, math, physics, or a related degree with 1+ years of industry experience
Strong grasp of computer architecture, data structures, system software, and machine learning fundamentals.
Proficient in C/C++ and Python development in Linux environments and using standard development tools.
Experience implementing algorithms in high-level languages such as C/C++ and Python.
Experience implementing algorithms for specialized hardware such as FPGAs, DSPs, GPUs, and AI accelerators using libraries such as CUDA, etc.
Experience in implementing operators commonly used in ML workloads—GEMMs, Convolutions, BLAS, SIMD operators for operations like softmax, layer normalization, pooling, etc.
Experience with development for embedded SIMD vector processors such as Tensilica.
Self-motivated team player with a strong sense of ownership and leadership.
Preferred:
Prior startup, small team, or incubation experience.
Experience with ML frameworks such as TensorFlow and/orPyTorch.
Experience working with ML compilers and algorithms, such as MLIR, LLVM, TVM, Glow, etc.
Experience with a deep learning framework (such as PyTorch or TensorFlow) and ML models for CV, NLP, or recommendation
Work experience at a cloud provider or AI compute/subsystem company.
Ready to apply?
Apply to PhizenixAt Prodigal, we are building AI Agents for loan servicing and collections. Founded in 2018 by IITB alumni, our journey began with one bold mission: to eradicate the inefficiencies and confusion that have plagued the lending and collections industry for decades. We are backed by Y Combinator, Accel and Menlo Ventures.
Today, we stand at the forefront of a seismic shift in the industry, building Agentic AI applications for consumer finance. Powered by our cutting-edge platform, Prodigal’s Intelligence Engine (PIE), we’re creating the next-generation agentic workforce - one that empowers companies to achieve unprecedented levels of operational excellence and intelligence.
With over half a billion consumer finance interactions processed and a growing impact on more than 100 leading companies across North America, we’ve established ourselves as the go-to partner for organizations that demand more from their AI solutions. Our unparalleled experience, coupled with our trusted customer relationships, uniquely positions us to build Agentic AI applications that will revolutionize the future of consumer finance.
At Prodigal, we are driven by a singular, unrelenting purpose: to transform how consumer finance companies engage with their customers and, in turn, drive successful outcomes for all.
We're seeking a Machine Learning Lead to join our team in building cutting-edge products that shape the future of consumer finance. As a member of our team, you will oversee complex technical problems, build new features, and improve existing products. Our teams are constantly pushing the boundaries of applied intelligence in consumer finance, and we're looking for passionate individuals who can help us advance us further. If you're interested in leading a world-class team of engineers and researchers to work on exciting projects that have a significant impact, we encourage you to apply.
Responsibilities:
- Partner with the CTO to drive the team's goals and technical direction to pursue opportunities that make the organization more efficient
- Effectively communicate complex features and systems in detail
- Understand industry & company-wide trends to help assess & develop new technologies
- Partner with the CTO to lead long-term technical vision and roadmap for Machine Learning and the entire organization
- Suggest, collect, and synthesize requirements and create an effective feature roadmap
- Design and develop Machine learning products and services leveraging AI (LLMs, Agentic AI, classical ML, the modern NLP stack, etc)
- Architect and implement data pipelines for ML model training. Lead scalable software systems development to deploy ML models into production systems, ensuring high performance and reliability.
- Stay updated on ML research and the ever-changing Gen AI landscape, identifying opportunities for innovation.
- Effectively collaborate with cross-functional teams to deliver high-quality solutions on time. Guide team members in contributing to ML design discussions for new projects.
Requirements:
- Extensive experience, 5+ years in software development, with a focus on machine learning and data science in a tech company.
- Proven track record of delivering high-quality ML products in a fast-paced, agile environment.
- Deep understanding of machine learning algorithms with hands-on experience in developing and deploying machine learning models at scale.
- Strong coding skills in Python. Familiarity with machine learning libraries such as PyTorch and sci-kit-learn. Experience with data manipulation and analysis tools like Pandas and Spark.
- Strong communication and leadership skills, with the ability to effectively collaborate with cross-functional teams and mentor junior engineers.
Preferred Qualifications:
- Experience with cloud services (AWS), Databricks, and building scalable, distributed systems.
Job Benefits
- GenAI experience – Work directly in the innovative field of GenAI, shaping groundbreaking projects that redefine consumer finance intelligence.
- World-class team - You'll get the chance to learn from (and teach) some of the brightest and most skilled people you'll ever meet. Our team members have been part of BCG, Deloitte, EY, Blackstone, Meta, Amazon and are IIT, IIM, BITS alumnus.
- Continuous education - As relentless seekers of knowledge, we sponsor and support any training materials, books, courses, and exam fees for upskilling yourself in areas related to your role - but that's not where it ends. If you make a good case for some extra learning, we're delighted to foot the tab.
- Food at the office – Meals are on us. We won't let your stomach grumble while you hustle.
- Health insurance - Health always comes first. The health of your family is as important to us as it is to you. We offer insurance coverage for both you and your family.
- Flexible schedule - We're not a "clock in, clock out" company. Morning person? Start work while the world's still sleeping. Night owl? Ramp things up while others are winding down. You're fully trusted to create the right conditions for your own personal peak productivity. We only ask that you be available to your teammates for seamless collaboration.
- Generous leave policy - Take all the time you need to recharge your batteries - no cap on vacation here. Because a rested, relaxed, and refreshed mind is a happy and effective mind.
- Recreation & team activities – We regularly indulge in friendly football, table tennis, cooking sessions, and challenge each other to do those extra push-ups or chug that 4th drink (of course, that’s Nimbu Pani).
Meet Sangram - (Cofounder and CTO) and hear his vision for Prodigal below (01:38)
From day 1, Prodigal has been defined by talented, humble, and hungry leaders and we want this mindset and culture to continue to blossom from top to bottom in the company. If you have an entrepreneurial spirit and want to work in a fast-paced, intellectually-stimulating environment where you will be pushed to grow, then please reach out because we are looking to build a transformational company that reinvents one of the biggest industries in the US.
To learn more about us - please visit the following:
Our Story - https://www.prodigaltech.com/our-story
What shapes our thinking - https://link.prodigaltech.com/our-thesis
Ready to apply?
Apply to Prodigal
Staff Software Engineer -ML/AI
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Lookout, Inc. is a globally recognized cybersecurity leader delivering advanced protection for the most vulnerable element of any enterprise security strategy — human error and manipulation. Cloud-native by design, the Lookout platform offers rapid, scalable deployment and simplified security operations, defending the frontline of human-centric attacks—the mobile device. Attackers now target the human element more than ever, with mobile devices providing the most direct path to their victims. Using social engineering techniques that exploit basic human instincts like trust, curiosity, and urgency, they deceive users into revealing sensitive credentials, allowing them to slip past legacy security solutions.
Lookout Endpoint Detection and Response (EDR) continuously monitors mobile endpoints for signs of human-centric attacks, as well as traditional malware, software vulnerabilities, and other anomalous activity. It uses advanced threat detection techniques, including artificial intelligence (AI) and behavioral analysis, to identify threats before they escalate across the enterprise. Learn more at www.lookout.com and follow us on the Lookout Blog, LinkedIn, and X.
Lookout’s backend system supports a massive volume of data and an increasingly high level of demand, from data ingestion to delivery to dynamic analysis. We’re looking for talented and motivated engineers to build core components and services, as well as to contribute to evolving the architecture. We’re a small team working on a very large, modern system with a user base of millions, so you’ll get to work on a cutting-edge product and service on a large scale. We’re responsible for building and maintaining several of the services powering the various Lookout applications..
What you’ll do:
- You will be part of a dynamic and technically diverse group of engineers, where you will get to contribute, influence, learn and grow top notch technical skill sets, while building key features for our customers.
- Own the full machine learning lifecycle, from initial research and design to production deployment, monitoring, and continuous retraining.
- Establish and implement robust frameworks to train, evaluate, stress-test, and monitor ML/AI systems, driving continuous improvement and preventing model drift.
- Address and navigate real-world scale and performance challenges, ensuring all ML/AI models and systems are efficient, robust, and maintain target quality/latency under production constraints.
- Set technical direction as a senior Individual Contributor (IC) and mentor junior engineers.
- Quality is the forefront of all we do, so you will assist with improving all forms of automated testing (unit, integration, functional etc).
- We believe in, and practice, end to end service ownership, so you will fully participate in the ownership of your services and components, including on-call duties.
What we’re looking for:
- BS/MS in Computer Science or related field/degree with at least 5-8 years of work experience.
- A proven track record of architecting and deploying practical, high-impact ML/AI systems over multiple years, translating complex models into robust, real-world solutions.
- Experience working cross-functionally with data engineers, platform engineers, and product stakeholders to bring ML/AI systems to life.
- Expert proficiency in Python and strong software engineering skills, including the ability to write reliable, production-grade code. In-depth experience with major ML/Deep Learning frameworks: PyTorch, TensorFlow, scikit-learn.
- Familiarity with modern AI/ML stacks like Hugging Face and LangChain.
- Deep expertise in a wide range of standard ML algorithms, including classification, clustering, regression, and deep learning models.
- Hands-on experience with the LLM/RAG stack components: embeddings, knowledge graphs, vector databases, retrieval strategies, and prompt engineering.
- Proven ability to measure and optimize model efficacy using statistical methods.
- Hands-on experience with production ML infrastructure, including feature stores, model management, training/serving pipelines (MLOps), and monitoring tools.
- Up-to-date with new advances in NLP, LLMs and agent-frameworks.
- Strong grasp of software engineering fundamentals and algorithms.
- Experience with implementing secure, scalable API services.
Bonus Points:
- Practical experience applying advanced techniques to enhance model efficiency, including model distillation (creating smaller, faster student models) and model quantization (reducing memory footprint and latency).
- Experience with efficient Large Language Model (LLM) fine-tuning methods like LoRA and other PEFT techniques.
- Experience working with coding agents (Cursor, Copilot, Claude Code etc..)
- Experience with event streaming frameworks, technologies, patterns and architectures (particularly Kafka or similar)
- Professional programming experience with Scala and Golang
- Experience with serverless architectures on AWS, GCP.
- Experience with Kubernetes, container technology (Docker, ECS, EKS).
Ready to apply?
Apply to Lookout Inc
Lookout, Inc. is a globally recognized cybersecurity leader delivering advanced protection for the most vulnerable element of any enterprise security strategy — human error and manipulation. Cloud-native by design, the Lookout platform offers rapid, scalable deployment and simplified security operations, defending the frontline of human-centric attacks—the mobile device. Attackers now target the human element more than ever, with mobile devices providing the most direct path to their victims. Using social engineering techniques that exploit basic human instincts like trust, curiosity, and urgency, they deceive users into revealing sensitive credentials, allowing them to slip past legacy security solutions.
Lookout Endpoint Detection and Response (EDR) continuously monitors mobile endpoints for signs of human-centric attacks, as well as traditional malware, software vulnerabilities, and other anomalous activity. It uses advanced threat detection techniques, including artificial intelligence (AI) and behavioral analysis, to identify threats before they escalate across the enterprise. Learn more at www.lookout.com and follow us on the Lookout Blog, LinkedIn, and X.
Lookout’s backend system supports a massive volume of data and an increasingly high level of demand, from data ingestion to delivery to dynamic analysis. We’re looking for talented and motivated engineers to build core components and services, as well as to contribute to evolving the architecture. We’re a small team working on a very large, modern system with a user base of millions, so you’ll get to work on a cutting-edge product and service on a large scale. We’re responsible for building and maintaining several of the services powering the various Lookout applications..
What you’ll do:
- You will be part of a dynamic and technically diverse group of engineers, where you will get to contribute, influence, learn and grow top notch technical skill sets, while building key features for our customers.
- Own the full machine learning lifecycle, from initial research and design to production deployment, monitoring, and continuous retraining.
- Establish and implement robust frameworks to train, evaluate, stress-test, and monitor ML/AI systems, driving continuous improvement and preventing model drift.
- Address and navigate real-world scale and performance challenges, ensuring all ML/AI models and systems are efficient, robust, and maintain target quality/latency under production constraints.
- Set technical direction as a senior Individual Contributor (IC) and mentor junior engineers.
- Quality is the forefront of all we do, so you will assist with improving all forms of automated testing (unit, integration, functional etc).
- We believe in, and practice, end to end service ownership, so you will fully participate in the ownership of your services and components, including on-call duties.
What we’re looking for:
- BS/MS in Computer Science or related field/degree with at least 5-8 years of work experience.
- A proven track record of architecting and deploying practical, high-impact ML/AI systems over multiple years, translating complex models into robust, real-world solutions.
- Experience working cross-functionally with data engineers, platform engineers, and product stakeholders to bring ML/AI systems to life.
- Expert proficiency in Python and strong software engineering skills, including the ability to write reliable, production-grade code. In-depth experience with major ML/Deep Learning frameworks: PyTorch, TensorFlow, scikit-learn.
- Familiarity with modern AI/ML stacks like Hugging Face and LangChain.
- Deep expertise in a wide range of standard ML algorithms, including classification, clustering, regression, and deep learning models.
- Hands-on experience with the LLM/RAG stack components: embeddings, knowledge graphs, vector databases, retrieval strategies, and prompt engineering.
- Proven ability to measure and optimize model efficacy using statistical methods.
- Hands-on experience with production ML infrastructure, including feature stores, model management, training/serving pipelines (MLOps), and monitoring tools.
- Up-to-date with new advances in NLP, LLMs and agent-frameworks.
- Strong grasp of software engineering fundamentals and algorithms.
- Experience with implementing secure, scalable API services.
Bonus Points:
- Practical experience applying advanced techniques to enhance model efficiency, including model distillation (creating smaller, faster student models) and model quantization (reducing memory footprint and latency).
- Experience with efficient Large Language Model (LLM) fine-tuning methods like LoRA and other PEFT techniques.
- Experience working with coding agents (Cursor, Copilot, Claude Code etc..)
- Experience with event streaming frameworks, technologies, patterns and architectures (particularly Kafka or similar)
- Professional programming experience with Scala and Golang
- Experience with serverless architectures on AWS, GCP.
- Experience with Kubernetes, container technology (Docker, ECS, EKS).
Ready to apply?
Apply to Lookout
Join AlphaSense India Talent Community
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About AlphaSense:
The world’s most sophisticated companies rely on AlphaSense to remove uncertainty from decision-making. With market intelligence and search built on proven AI, AlphaSense delivers insights that matter from content you can trust. Our universe of public and private content includes equity research, company filings, event transcripts, expert calls, news, trade journals, and clients’ own research content.
The acquisition of Tegus by AlphaSense in 2024 advances our shared mission to empower professionals to make smarter decisions through AI-driven market intelligence. Together, AlphaSense and Tegus will accelerate growth, innovation, and content expansion, with complementary product and content capabilities that enable users to unearth even more comprehensive insights from thousands of content sets. Our platform is trusted by over 6,000 enterprise customers, including a majority of the S&P 500. Founded in 2011, AlphaSense is headquartered in New York City with more than 2,000 employees across the globe and offices in the U.S., U.K., Finland, India, Singapore, Canada, and Ireland. Come join us!
In India, we have our teams based in Pune, Mumbai, Delhi and, Bangalore. We pride ourselves on being client-focused and collaborative, on the pioneering edge of technology. We also have fun. Whether it’s office happy hours, team outings, or game nights, we believe in working with people we like to hang out with.
Ideal candidate traits
If you identify as a team player and you are humble, hungry, and smart — we would love to get to know you. We believe these qualities to be vital to building a strong, productive, and collaborative work environment, where everyone is committed to achieving common goals and working towards shared success.
We are looking for people who are willing to learn from others, who can put their egos aside and prioritise the needs of the team. You should also be highly motivated, driven to succeed, and always looking for ways to improve. We value emotional intelligence, excellent communication skills, and a collaborative spirit that enables them to build strong relationships with teammates and work effectively towards shared goals.
At AlphaSense we are committed to fostering a work culture that encourages these qualities and values the contributions of team players who exhibit them. We seek to match the ambition of ideal team players by offering opportunities for personal and professional growth, providing the resources and support necessary to achieve their goals, and creating an environment where hard work, dedication, and teamwork are celebrated and rewarded. At AlphaSense we are building teams of ideal players who embody the core values of Sisu, driving the company’s success and helping us to create a positive impact on the world.
Technologies that we work with:
Frontend
ReactJS, TypeScript, Micro Frontends
Applications
NodeJS, TypeScript, GraphQL, Java 17, Spring Boot, Python, FastAPI
Backend
Java 17, Spring Boot, Python, FastAPI, Kafka
Search and AI
Apache Solr, Elasticsearch, Vector Search, ML, LLM, Pytorch, Tensorflow
Cloud architecture
AWS, GCP, Kubernetes, Crossplane, Argo CD
Quality & reliability
Cypress, Selenium, Selenide, Playwright, Rest Assured, K6, Prometheus, Loki, Grafana
Ready to Make an Impact?
Join our talent community, hear about exciting career opportunities, and get tailored job recommendations based on your interests.
If you’re looking for a challenge, if you love finding things that need interesting solutions, AlphaSense is a great place to come. It is a place for builders, for people who want to create the next thing.
Want to hear more?
Contact us and let’s figure out together if we can find a common path. Tell us about yourself and your background in your own words.
AlphaSense is an equal-opportunity employer. We are committed to a work environment that supports, inspires, and respects all individuals. All employees share in the responsibility for fulfilling AlphaSense’s commitment to equal employment opportunity. AlphaSense does not discriminate against any employee or applicant on the basis of race, color, sex (including pregnancy), national origin, age, religion, marital status, sexual orientation, gender identity, gender expression, military or veteran status, disability, or any other non-merit factor. This policy applies to every aspect of employment at AlphaSense, including recruitment, hiring, training, advancement, and termination.
In addition, it is the policy of AlphaSense to provide reasonable accommodation to qualified employees who have protected disabilities to the extent required by applicable laws, regulations, and ordinances where a particular employee works.
Recruiting Scams and Fraud
We at AlphaSense have been made aware of fraudulent job postings and individuals impersonating AlphaSense recruiters. These scams may involve fake job offers, requests for sensitive personal information, or demands for payment. Please note:
- AlphaSense never asks candidates to pay for job applications, equipment, or training.
- All official communications will come from an @alpha-sense.com email address.
- If you’re unsure about a job posting or recruiter, verify it on our Careers page.
If you believe you’ve been targeted by a scam or have any doubts regarding the authenticity of any job listing purportedly from or on behalf of AlphaSense please contact us. Your security and trust matter to us.
Ready to apply?
Apply to AlphaSense
Staff Machine Learning Engineer
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About AiDASH
AiDASH is an enterprise AI company and the leading provider of vegetation risk intelligence for electric utilities. Powered by proprietary VegetationAI™ technology, AiDASH delivers a unified remote grid inspection and monitoring platform that uses a SatelliteFirst approach to identify and address vegetation and other threats to the grid. With a prevention-first strategy to mitigate wildfire risk and minimize storm impacts, AiDASH helps more than 140 utilities reduce costs, improve reliability, and lower liability across their networks. AiDASH exists to safeguard critical utility infrastructure and secure the future of humanAIty™. Learn more at www.aidash.com.
We are a Series C growth company backed by leading investors, including Shell Ventures, National Grid Partners, G2 Venture Partners, Duke Energy, Edison International, Lightrock, Marubeni, among others. We have been recognized by Forbes two years in a row as one of “America’s Best Startup Employers.” We are also proud to be one of the few software companies in Time Magazine’s “America’s Top GreenTech Companies 2024”. Deloitte Technology Fast 500™ recently ranked us at No. 12 among San Francisco Bay Area companies, and No. 59 overall in their selection of the top 500 for 2024.
Join us in Securing Tomorrow!
The Role
We’re looking for a seasoned Staff Machine Learning Engineer to shape and scale the backbone of our production ML ecosystem. In this role, you will architect high-performing ML systems that power our geospatial intelligence platform, transforming large-scale satellite and aerial imagery into actionable insights. You’ll lead end-to-end ownership—from model deployment and MLOps to infrastructure design—while partnering closely with data science, platform engineering, and product teams to deliver reliable, scalable, and cost-efficient ML solutions. If you thrive at the intersection of deep technical expertise, system design, and cross-functional collaboration, this role is for you.
How you'll make an impact:
ML System Architecture & Production Deployment
- Design, build, and maintain end-to-end ML pipelines for batch processing of satellite and aerial imagery
- Deploy and scale ML models in production on AWS infrastructure, leveraging services like SageMaker, Bedrock,or custom-built solutions
- Implement MLflow for experiment tracking, model versioning, and model registry management
- Architect batch inference systems optimized for throughput and cost-efficiency
- Work with geospatial data formats and coordinate reference systems
- Collaborate with data scientists to transition models from research to production
- Partner with platform engineering to build scalable compute, GPU clusters, and storage layers
ML Operations & Reliability
- Implement comprehensive model monitoring systems to track performance degradation and data drift
- Design and execute canary deployments and A/B testing frameworks for safe model rollouts
- Build active learning pipelines to continuously improve model performance with minimal labeling effort
- Establish model evaluation frameworks and performance benchmarking processesCreate alerting and observability systems for production ML workloads
Technical Leadership
- Mentor ML engineers and data scientists on best practices for production ML
- Drive technical decision-making on ML infrastructure and tooling
- Collaborate with platform and data engineering teams to optimize the ML stack
- Establish engineering standards and contribute to architectural roadmaps
What we’re looking for:
- 5+ years of experience in machine learning engineering with 2+ years in a senior or lead capacity
- Proven track record deploying and maintaining ML systems in production using AWS services (SageMaker,Lambda, ECS/EKS, S3, etc.)
- Strong hands-on experience with tools like MLflow, WandB, or similar for experiment tracking and model management
- Deep expertise in image segmentation and computer vision techniques using frameworks like PyTorch or TensorFlow
- Production experience with ensemble models (xgboost, lightgbm, RF)
ML Operations Expertise
- Experience implementing model monitoring, drift detection, and alerting systems
- Hands-on experience with canary deployments, A/B testing and Shadow deployments for ML models
- Knowledge of active learning strategies and human-in-the-loop ML systems
- Strong understanding of model evaluation metrics, bias detection, and performance analysis
Technical Skills
- Expert-level Python programming with ML libraries (scikit-learn, PyTorch/TensorFlow, NumPy, pandas, etc)
- Experience with distributed batch processing frameworks (Airflow, Step Functions, Argo Workflows, Spark,Dask, Ray or similar)
- Proficiency with AWS ML ecosystem and infrastructure-as-code (Terraform, CloudFormation)
- Hands-on experience with dataset versioning tools such as DVC, LakeFS, Delta Lake, Quilt, or Pachyderm
- Strong software engineering fundamentals: unit/integration testing, CI/CD, version control, observability, designpatterns
- Experience with containerization (Docker, Kubernetes) for model deployment
- Good to have experience with ML Orchestration tools like Kubeflow, Vertex AI, etc
- Nice to have experience with GPUs: scheduling GPU jobs, optimizing GPU performance, memory profiling
We are proud to be an equal-opportunity employer. We are committed to embracing diversity and inclusion in our hiring practices, and we promote a work environment where everyone, from any race, color, religion, sex, sexual orientation, gender identity, or national origin, can do their best work.
Read our Privacy Policy here: https://www.aidash.com/policy/privacy-policy/
Ready to apply?
Apply to AiDASH, Inc.
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?
Apply to Capco
Why Valtech? We’re the experience innovation company - a trusted partner to the world’s most recognized brands. To our people we offer growth opportunities, a values-driven culture, international careers and the chance to shape the future of experience.
The Opportunity
At Valtech, you’ll find an environment designed for continuous learning, meaningful impact, and professional growth. Whether you're pioneering new digital solutions, challenging conventional thinking or building the next generation of customer experiences, your work will help transform industries.
We are proud of:
- The work we do and the innovation we drive
- Our values of share, care and dare
- A workplace culture that fosters creativity, diversity and autonomy
- Our borderless, global framework, which enables seamless collaboration
The Role
As a Senior Data Scientist, you are passionate about experience innovation and eager to push the boundaries of what’s possible. You bring 4+ years of experience, a growth mindset and a drive to make a lasting impact.
You will thrive in this role if you are:
- A curious problem solver who challenges the status quo
- A collaborator who values teamwork and knowledge-sharing
- Excited by the intersection of technology, creativity and data
- Experienced in Agile methodologies and consulting (a plus)
Role & Responsibilities:
Generative AI Innovation & Strategy
- Lead GenAI Initiatives: Spearhead the identification of business scenarios where Generative AI (LLMs, GANs, Diffusion models) can be effectively applied to create tangible value.
- R&D & Prototyping: Research, design, and prototype cutting-edge approaches, exploring existing scientific research to inform solution development.
- Feasibility Analysis: Evaluate the technical and economic feasibility of Generative AI solutions for real-world client use cases.
- Vision Shaping: Collaborate with Product Managers and stakeholders to shape a clear, forward-looking vision of AI technology and its practical applications.
Technical Execution & Implementation
- End-to-End Development: Implement and validate AI solutions for diverse business challenges, writing production-ready code using best engineering practices.
- Optimization: Optimize deep learning models for production environments to ensure scalability and latency requirements are met.
- Cross-Functional Collaboration: Collaborate closely with the ML Engineering team throughout all stages of the lifecycle, from initial research to final implementation.
- Data Strategy: Oversee the data mining process, including data collection, cleansing, and exploratory analysis to support model training and fine-tuning.
Must Have
To be considered for this role, you must meet the following essential qualifications:
- Total Experience: Minimum of 4+ years in Data Science and Analytics.
- Specialized Experience: Minimum 3+ years focused specifically on developing generative models (LLMs, GANs, VAEs, Diffusion models) and Deep Learning.
- Education: Bachelor’s or Master’s Degree in Computer Science, Mathematics, Applied Statistics, or a related field.
Technical Skills
- Core AI/ML: Expertise in Computer Vision and NLP, with specific experience handling multimodal data (images, text, audio).
- GenAI Stack: Familiarity with Gemini, OpenAI GPT-x, open-source LLMs (Llama, Mistral, etc.), and experience in fine-tuning models (PEFT, LoRA).
- Retrieval-Augmented Generation (RAG): Expertise in designing RAG architectures to ground LLM responses in proprietary data.
- Vector Databases: Proficiency with vector stores such as Pinecone, Milvus, Weaviate, or ChromaDB for efficient semantic search and retrieval.
- Prompt Engineering: Advanced skills in prompt optimization, chain-of-thought reasoning, and framework usage (e.g., LangChain, LlamaIndex).
- Programming: Strong programming skills in Python with proven ability to write clean, production-ready code.
- Frameworks: Proficiency with deep learning frameworks such as PyTorch or TensorFlow.
- Cloud: Hands-on experience with at least one major cloud platform (AWS, Azure, or GCP).
Soft Skills
- Communication: Excellent fluency in English (B2+ or higher) with the ability to explain complex technical concepts to non-technical audiences.
- Problem Solving: A strategic thinker capable of devising holistic solutions for complex customer issues.
Nice to Have (Preferred Qualifications)
- Experience with MLOps tools (e.g., MLflow, Kubeflow) and practices for deploying and monitoring AI models.
- Responsible AI: Knowledge of AI ethics, bias detection, and safety guardrails (e.g., NeMo Guardrails) for deploying LLMs securely.
- API Development: Experience wrapping models in APIs using FastAPI or Flask for integration with frontend applications.
- Knowledge of Reinforcement Learning (RLHF) and self-supervised learning approaches.
- Experience with emerging Generative AI architectures.
If you do not meet all the listed qualifications or have gaps in your experience, we still encourage you to apply. At Valtech, we recognize that talent comes in many forms, and we value diverse perspectives and a willingness to learn.
Commitment to reaching all kinds of people
We design experiences that work for all kinds of people - and that starts with our own teams. At Valtech, we’re intentional about building an inclusive culture where everyone feels supported to grow, thrive and achieve their goals. No matter your background, you belong here. Explore our Diversity & Inclusion site to see how we’re creating a more equitable Valtech for all.
The Benefits
This is a Full-Time position based in Bengaluru.
Beyond a competitive compensation package, we offer:
- Flexibility, with hybrid work options (country-dependent)
- Learning and development, with access to cutting-edge tools, training and industry experts.
Our benefits are tailored to each location. Your Talent Partner will provide full details during the hiring process.
Your application process
Once you apply, our Talent Acquisition team will review your application. If your skills and experience align with the role, we’ll reach out for next steps.
⚠️ Beware of recruitment fraud: Only engage with official Valtech email addresses ending in @valtech.com.
We are committed to inclusion and accessibility. If you need reasonable accommodations during the interview process, please either indicate it in your application or let your Talent Partner know.
About Valtech
Valtech is the experience innovation company that exists to unlock a better way to experience the world. By blending crafts, categories, and cultures, we help brands unlock new value in an increasingly digital world.
At the intersection of data, AI, creativity, and technology, we drive transformation for leading organizations, including L’Oréal, Mars, Audi, P&G, Volkswagen Dolby, and more.
At Valtech, we don’t just talk about transformation. We make it happen. Our people are the heart of our success, and we foster a workplace where everyone has the support to thrive, grow and innovate.
Are you ready to create what’s next? Join us.
Ready to apply?
Apply to Valtech
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