About the team

• ML infrastructure: Help build a first-class machine learning platform from the ground up which manages the entire model lifecycle - feature engineering, model training, versioning, deployment, online serving/evaluation, and monitoring prediction quality.
• Data analysis and feature engineering: Apply your expertise to identify and generate features that can be leveraged by multiple use cases and models.
• Model training with batch and real-time prediction scenarios: Use machine learning and statistical modelling techniques such as Decision Trees, Logistic Regression, Neural Networks, Bayesian Analysis and others to develop and evaluate algorithms for improving product/system performance, quality, and accuracy.
• Production operations: Low-level systems debugging, performance measurement, and optimisation on large production clusters.
  Collaboration with cross-functional teams: Partner with product managers, data scientists, and other engineers to deliver impactful solutions.
  Staying ahead of the curve: Continuously learn and adapt to emerging technologies and industry trends.

• Bachelors, Masters, or PhD in Computer Science, Statistics, or a related field.
• Experience in applied machine learning on real use cases (bonus points for ad tech-related use cases). Min 5 years of total experience.
• Great coding skills and strong software development experience (we use Spark, Python, Java).
• Familiarity with real-time evaluation of models with low latency constraints.
• Familiarity with distributed ML frameworks such as Spark-MLlib, TensorFlow, etc.
• Ability to work with large scale computing frameworks, data analysis systems, and modelling environments. Examples include Spark, Hive, NoSQL stores such as Aerospike and ScyllaDB.
• Ad tech background is a plus.
• AI growth mindset / AI Literacy
  
  
  

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).

Role 

We are looking for an experienced Staff Machine Learning Engineer to join our Engineering team. This role is based in Bangalore, reporting to the Senior Engg. Manager - Data + AI.

You will be responsible for designing and developing large scale ML Systems that analyze massive volumes of network data to detect anomalies, threats, and patterns in near real-time. You’ll solve complex real-world business problems by partnering closely with data architects and product teams to deliver impactful automation and intelligence, including the design and orchestration of specialized autonomous agents.

What you’ll do (Role Expectations)

• Build and maintain large-scale distributed systems to support the full ML lifecycle, including data collection, feature engineering, and Agentic AI components like agent workflows and real-time serving
• Solve complex business problems such as threat detection by collaborating with data architects and product teams to build multi-agent solutions that automate analysis and decisioning
• Partner with cross-functional teams to assess requirements, manage scheduling, and lead the development and debugging of agent-based systems
• Support the rollout and monitoring plans for production-grade ML systems to ensure performance, observability, and scalability

Who You Are (Success Profile)

• You thrive in ambiguity. You're comfortable building the path as you walk it. You thrive in a dynamic environment, seeing ambiguity not as a hindrance, but as the raw material to build something meaningful.
• You act like an owner. Your passion for the mission fuels your bias for action. You operate with integrity because you genuinely care about the outcome. True ownership involves leveraging dynamic range: the ability to navigate seamlessly between high-level strategy and hands-on execution.
• You are a problem-solver. You love running towards the challenges because you are laser-focused on finding the solution, knowing that solving the hard problems delivers the biggest impact.
• You are a high-trust collaborator. You are ambitious for the team, not just yourself. You embrace our challenge culture by giving and receiving ongoing feedback—knowing that candor delivered with clarity and respect is the truest form of teamwork and the fastest way to earn trust.
• You are a learner. You have a true growth mindset and are obsessed with your own development, actively seeking feedback to become a better partner and a stronger teammate. You love what you do and you do it with purpose.

What We’re Looking for (Minimum Qualifications)

• 5+ years of experience as an AI-ML Engineer with technical proficiency in Java, Springboot, Python, and PyTorch or TensorFlow
• Proven experience writing high-performance queries for large-scale analytics platforms such as Azure Data Explorer (ADX/Kusto) or Google BigQuery, including partitioning-aware patterns
• Deep expertise in designing and deploying anomaly detection using tree-based models, statistical techniques, and streaming ML approaches
• Hands-on experience developing multi-agent orchestration, agent-to-agent communications, and autonomous decision-making workflows
• Strong technical background with distributed infrastructure and public cloud platforms like Azure, GCP, or AWS

What Will Make You Stand Out (Preferred Qualifications)

• A track record of shipping end-to-end applications at scale that process billions of events
• Willingness to work across the full spectrum of Big Data and AI-based solutions
• Hands-on experience with SOTA AI frameworks, prompt engineering, and complex agent architectures

#LI-Bangalore #LI-AN4

About Inizio Ignite:

Inizio Ignite is the global advisory partner for health and life sciences, encompassing connected expertise across Research Partnership, Putnam, Vynamic, and STEM. Guided by purpose, passion, and precision, we collaborate with clients to ignite impact, accelerate performance, and deliver lasting change for patients. By uniting strategy, insights, and innovation with a unique depth and breadth of expertise, we drive transformation and shape the future of health.

Company Descriptor

Inizio Ignite is the global advisory partner for health and life sciences, encompassing connected expertise across Research Partnership, Putnam, Vynamic, and STEM. Guided by purpose, passion, and precision, we collaborate with clients to ignite impact, accelerate performance, and deliver lasting change for patients. By uniting strategy, insights, and innovation with a unique depth and breadth of expertise, we drive transformation and shape the future of health. Our Research Partnership healthcare market research team provides research and insights to inform and power healthcare decisions. Serving a variety of clients across the lifecycle, our expertise includes data, research & insights (proprietary syndicated and custom research) and brand tracking (ATU). Proudly part of Inizio – the market-leading commercialization partner for health and life sciences. From early-stage development to loss of exclusivity, we simplify complexity, unlock value, and make collaboration seamless at every pivotal moment – supporting confident, insight-driven decisions that move innovation forward. 

Role Overview

The Data Delivery & Dashboards Executive role will report into the Dashboard Manager. The Data Delivery & Dashboards Executive will be a key member of the newly formed India-based Data Management & Delivery Hub, supporting quantitative healthcare market research projects across global markets. As a Dashboard Developer Executive, you build and maintain high impact dashboards and data visualizations that transform raw market research data into actionable insights. You’ll collaborate with researchers, analysts, and engineers to ensure data flows seamlessly from collections to visual storytelling. You will also support the team in delivering insightful, user-friendly dashboards through automated tools and off-the-shelf solutions. This is a fantastic opportunity to develop your skills in data management, quality assurance, and data visualisation, while working alongside an experienced team in a dynamic, global environment. Skill Set required

What you'll be doing

Brand Equity tracking support with our in-house platform:

• Maintain the pipeline for the project data process flow (this includes receival of data into in-hosue Tool, through the data processing stage into the storage mart, through the python utilities into required outputs)
• Maintain and update python utilities when required due to changes from the research team
• Manage and rectify when failures occur in the pipeline, liaising with both the data providers, research team and developers on the dashboard
• Manage the storage mart and data warehouse
• Support team with edits in-house platform

Data Quality Checks:
Assist in performing detailed quality control checks on large and complex datasets to ensure accuracy, completeness, and consistency.

Data Transformation & Standardisation:
Support the transformation and standardisation of data files to align with internal data structures, project needs, and client-specific formats.

Dashboard Support & Maintenance:
Assist in the creation, population, and maintenance of dashboards using off-the-shelf tools (e.g., Power BI, Tableau, or similar platforms), ensuring outputs are clear, accurate, and aligned with research objectives.

Data Delivery Management:
Help manage and organise the final delivery of data files and dashboards to internal teams and clients, ensuring timely and error-free execution.

Collaboration Across Teams:
Work closely with internal stakeholders including Development team, Data Processing, Scripting, Project Management and Research teams to ensure smooth handovers and integration of deliverables.

Documentation & Reporting:
Maintain clear documentation of processes, data transformation steps, and QC logs to support transparency, reproducibility, and audit-readiness.

Continuous Learning & Development:
Engage in training opportunities to build knowledge in healthcare data, market research workflows, dashboarding tools, and data handling best practices.

What you'll need

Your skills and experience:

Technical Expertise

• Atleast 5+ years expertise in languages like Python and SQL.
• Mastery in advanced Core Python (generators, decorators, OOP, async programming), architecture design.
• Proficient in libraries like Pandas - Joins, Melting, handling missing values, NumPy, TensorFlow etc.
• Proficient in SQL (PostgreSQL, MySQL).
• Understanding MVC/MVT, microservices, and system design principles.
• Experience in setup of data pipelines is highly desirable.
• Knowledge of high-performance framework (Django, FastAPI, Flask) is a plus.
• Cloud platform expertise (AWS, Azure, GCP), and building ETL/ELT pipelines.
• Experience in version control system.

Ideal candidate should be

• You are proactive, dedicated and enthusiastic, with a ‘can do’ attitude and approach
• You demonstrate a high level of accuracy and attention to detail, as well as strengths in organisation and prioritisation
• You are a collaborative team player who works well with colleagues
• You communicate ideas and issues in an effective, straightforward fashion
• Logical thinking and ability to troubleshoot errors or discrepancies in tabulated data.
• Ability to interpret tabulation specifications and apply them accurately.
• Problem-solving skills (particularly relating to situations requiring analytical judgement and establishing best practice solutions)
• You are highly motivated and want to seize opportunities to develop new skills and progress your career

Artificial Intelligence

Inizio may use AI technologies to support certain aspects of our recruitment process, but all hiring decisions are made by our human recruiting team. We are committed to fair, inclusive, and human-led hiring practices. Don't meet every requirement? That's okay! We are dedicated to building a diverse, inclusive, and authentic workplace. If you're excited about this role but your experience doesn't perfectly fit every qualification, we encourage you to apply anyway. You may be just the right person for this role or others.

About Inizio Ignite

We are Inizio Ignite, the global advisory partner for health and life sciences encompassing connected expertise across Research Partnership, Putnam, STEM, and Vynamic. Guided by purpose, passion, and precision, we collaborate with clients to ignite impact, accelerate performance, and deliver lasting change for patients. By uniting strategy, insights, and innovation with a unique depth and breadth of expertise, we drive transformation and shape the future of health. Proudly part of Inizio – the market-leading commercialization partner for health and life sciences. From early-stage development to loss of exclusivity, we simplify complexity, unlock value, and make collaboration seamless at every pivotal moment – helping healthcare leaders shape strategy and drive meaningful change. 

About the Role

We are seeking an experienced Data Science Manager to join our team at Inizio Ignite. The ideal candidate will bring deep machine learning expertise, strong GenAI and cloud competencies, and hands-on experience delivering analytical solutions that drive meaningful business impact for life sciences clients.

This leader will manage data scientists, oversee project delivery, partner with cross-functional teams, and shape the development of innovative AI/ML solutions.

What you'll be doing

Leadership & Delivery

• Lead and manage a team of data scientists, providing technical guidance, mentorship, and performance oversight.
• Own end-to-end delivery of data science and GenAI engagements for pharma/biotech clients.
• Translate business problems into analytical frameworks and ensure high-quality, timely project execution.
• Drive adoption of AI/ML capabilities across client engagements and internal initiatives.

Technical Responsibilities

• Architect, design, and review ML, statistical, and GenAI solutions, ensuring scalability, accuracy, and alignment with business objectives.
• Oversee the development, validation, and deployment of predictive models, NLP pipelines, and GenAI-based applications (e.g., summarization, insights automation, generative workflows).
• Lead cloud-based solution deployment (AWS, Azure, or GCP) including orchestration, MLOps best practices, and integration with enterprise systems.
• Ensure adherence to model governance, compliance, and responsible AI frameworks.

What you'll need

• Extensive experience in data science or advanced analytics roles, with at least 2–3 years in a leadership or managerial capacity.
• Ideally prior experience in pharmaceutical, biotech, or healthcare consulting is mandatory.
• Strong expertise in machine learning, NLP, deep learning, and GenAI (LLMs, prompt engineering, RAG, fine-tuning, embeddings).
• Hands-on experience with cloud platforms such as AWS, Azure, or GCP; exposure to MLOps frameworks preferred.
• Proficiency in Python, SQL, and common DS/ML libraries (TensorFlow, PyTorch, scikit-learn, Hugging Face, LangChain, etc.).
• Proven experience managing teams, delivering client projects, and presenting to senior stakeholders.
• Good to have understanding of pharma datasets (claims, RWE, clinical, medical insights, social data) and key use cases.
• Experience building GenAI solutions in production environments

Our Pledge

At Inizio, we value inclusivity, recognize the power of diversity, and inspire the next generation of change-makers. We are an equal opportunities employer and are committed to creating a dynamic work environment that values diversity, equity, and inclusion. We welcome all applications regardless of race, color, religion, gender identity, age, national origin, marital status, veteran status, genetic information, sexual orientation, or disability.

Artificial Intelligence

Inizio may use AI technologies to support certain aspects of our recruitment process, but all hiring decisions are made by our human recruiting team. We are committed to fair, inclusive, and human-led hiring practices. Don't meet every requirement? That's okay! We are dedicated to building a diverse, inclusive, and authentic workplace. If you're excited about this role but your experience doesn't perfectly align with every qualification, we encourage you to apply anyway.

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!

https://zetaglobal.com/press/?cat=press-releases 

See yourself at Twilio

Join the team as Twilio’s next Staff Machine Learning Engineer.

About the job

This position is needed to scope, design, and deploy machine learning systems into the real world, the individual will closely partner with Product & Engineering teams to execute the roadmap for Twilio’s AI/ML products and services.

You will understand customers need, build data products that works at a global scale and own end-to-end execution of large scale ML solutions. 

To thrive in this role, you must have a deep background in ML engineering, and a consistent track record of solving data & machine-learning problems at scale. You are a self-starter, embody a growth attitude, and collaborate effectively across organizations.

Responsibilities

In this role, you’ll:

• Build and maintain scalable machine learning solutions in production
• Train and validate both deep learning-based and statistical-based models considering use-case, complexity, performance, and robustness
• Demonstrate end-to-end understanding of applications and develop a deep understanding of the “why” behind our models & systems
• Partner with product managers, tech leads, and stakeholders to analyze business problems, clarify requirements and define the scope of the systems needed
• Work closely with data platform teams to build robust scalable batch and realtime data pipelines
• Collaborate with software engineers, build tools to enhance productivity and to ship and maintain ML models
• Drive high engineering standards on the team through mentoring and knowledge sharing
• Uphold engineering best practices around code reviews, automated testing and monitoring

Qualifications 

Twilio values diverse experiences from all kinds of industries, and we encourage everyone who meets the required qualifications to apply. If your career is just starting or hasn't followed a traditional path, don't let that stop you from considering Twilio. We are always looking for people who will bring something new to the table!

Required:

• 7+ years of applied ML experience with proficiency in Python
• Strong background in the foundations of Machine Learning and building blocks of modern Deep Learning
• Track record of building, shipping and maintaining Machine Learning models in production in an ambiguous and fast paced environment.
• Track record of designing and architecting large scale experiments and analysis to inform product roadmap.
• You have a clear understanding of frameworks like - PyTorch, TensorFlow, or Keras, why and how these frameworks do what they do
• Familiarity with ML Ops concepts related to testing and maintaining models in production such as testing, retraining, and monitoring.
• Demonstrated ability to ramp up, understand, and operate effectively in new application / business domains.
• You’ve explored modern data storage, messaging, and processing tools (Kafka, Apache Spark, Hadoop, Presto, DynamoDB etc.) and demonstrated experience designing and coding in big-data components such as DynamoDB or similar
• Experience working in an agile team environment with changing priorities
• Experience of working on AWS

Desired:

• Experience with Large Language Models

Location

This role will be remote, and based in India

Travel

We prioritize connection and opportunities to build relationships with our customers and each other. For this role, you may be required to travel occasionally to participate in project or team in-person meetings.

What We Offer

Working at Twilio offers many benefits, including competitive pay, generous time off, ample parental and wellness leave, healthcare, a retirement savings program, and much more. Offerings vary by location.

See yourself at Twilio

Join the team as Twilio’s next Senior Offensive Security Engineer

About the job

This position is needed to The Senior OffSec Engineer will be responsible for the day-to-day execution of penetration tests and contributing to larger Red Team campaigns. You move beyond simple scanning to manual exploitation and are beginning to automate your workflows.  

Responsibilities

In this role, you’ll:

• Full-Stack Penetration Testing: Perform manual and automated testing of web applications, APIs, and mobile apps (iOS/Android).
• Internal/External Network Audits: Conduct network and cloud level assessments with various tooling
• Vulnerability Validation: Triage and validate reports from automated scanners or bug bounty hunters to eliminate false positives and escalate true positives
• AI/LLM Probing: Perform initial prompt injection and jailbreak tests on AI prototypes, services, and applications using established checklists (OWASP Top 10 for LLMs).
• Technical Reporting: Draft high-quality reports that detail the "path to compromise" with clear, reproducible steps for developers.
• Tool Maintenance: Manage and update the team's testing infrastructure (e.g., Burp Suite, and basic C2 listeners).
• Remediation Support: Provide direct technical guidance to engineering teams on how to patch vulnerabilities like XSS, SQLi, and IDOR.
• Adversary Emulation: Design and lead multi-week Red Team operations that mimic specific threat actors (APTs) to test the SIRT detection capabilities.
• Custom Exploit Development: Build custom payloads, droppers, and obfuscated scripts to bypass EDR/AV and maintain stealth.
• AI Red Teaming Architecture: Build automated testing frameworks for AI systems (e.g., using PyRIT, Promptfoo, or Garak) to test for models related to sensitive data leakage.
• Cloud & Infrastructure Attacks: Execute sophisticated attacks against AWS/Azure/K8s, focusing on IAM misconfigurations and container escapes.
• Purple Teaming: Collaborate with SIRT and Detection Engineering to tune SIEM alerts based on the techniques used during an engagement.
• Strategic Bug Bounty Management: Oversee the organization's bug bounty program, identifying trends in submissions to suggest broad architectural security changes.

*Required:

• Experience: 3–5 years in offensive security, penetration testing, or a high-volume bug bounty background and track record of finding high/critical vulnerabilities in complex environments.
• Concepts: Expert Knowledge and  solid understanding of the MITRE ATT&CK matrix and the OWASP Top 10 for web applications and top 10 for LLMs, post exploitation (lateral movement, persistence, data exfiltration) and Adversarial ML.
• Tooling: Proficient in Burp Suite professional, Nmap, Metasploit, Wireshark etc... and AI security tools such as LangChain, TensorFlow for adversarial testing, as well as use of C2 frameworks (Cobalt Strike, Sliver, Havoc) or similar tools
• Scripting and Coding: Ability to write functional scripts in Python or Bash to automate repetitive testing tasks and proficiency in Python, C++, and scripting for creating custom offensive tooling that avoids signature-based detection.
• Certifications: Possession of advanced industry certifications such as OSCP, OSEP, OSWE, GXPN or similar
• Telecom expertise is preferred

Location

1. This role will be remote, and based in India. (Karnataka, Tamil Nadu, Telangana, Maharashtra, Delhi)

Travel 

We prioritize connection and opportunities to build relationships with our customers and each other. For this role, you may be required to travel occasionally to participate in project or team in-person meetings.

What We Offer

Working at Twilio offers many benefits, including competitive pay, generous time off, ample parental and wellness leave, healthcare, a retirement savings program, and much more. Offerings vary by location.

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.

Smartsheet is hiring a Senior Machine Learning Operations Engineer to architect our machine learning production lifecycle. Your mission is to maintain and deploy ML models to a scalable, reliable, and secure production environment. You will design and maintain the infrastructure, automation, and monitoring systems that ensure our AI products are high-performing and cost-effective.

You will report to our Director, Analytics Engineering & Data Governance and work from our Bangalore, India office. 

You Will:

Model and Pipeline Automation 

• Automate the deployment and retraining of ML models, from training through to production inference, by building and managing complete CI/CD/CT (Continuous Training) pipelines, adhering to MLOps best practices. 
• Build, fine-tune, or use pre-trained LLMs, deep learning models or traditional machine learning models.
• Evaluate and recommend AI or ML solutions for the product using any combination of vendor solutions and/or custom-built models.

Governance & Compliance

• Implement model versioning, lineage tracking, and auditing to ensure compliance with security and ethical standards.

Performance Monitoring

• Continuously monitor the health and performance of production machine learning models, proactively identifying and correcting model drift, staleness, and performance degradation. 
• Incorporate user feedback for iterative improvements and manage necessary model retraining cycles.

Cross-Functional Collaboration

• Act as the "glue" between Data Scientists (who build models) and Software Engineers (who consume them).
• Partner effectively with software engineers, product managers and business functions to integrate the machine learning solutions across smartsheet.

Architecture and Infrastructure Management

• Provision and manage scalable cloud infrastructure using Infrastructure as Code (IaC).
• Provide architectural guidance and mentorship to a team consisting of ML engineers, data scientists and analytics engineers.
• Distill complex ML concepts into easy-to-follow technical documentation.

You Have:

• 5+ years of experience with creating, deploying and scaling machine learning solutions in a cloud environment (eg. AWS, GCP, Azure) and ability to use tools such as SageMaker, Glue, Lambda, Docker etc. to create ML models and data pipelines. 
• 7+ years of programming experience in languages used in AI/ML (eg python, scala etc)
• 4+ years of experience in developing deep learning and traditional ML models using common frameworks like pytorch, tensorflow, huggingface, scikit-learn etc.
• Strong applied data science skills - ability to recognize data patterns, understand how and when to use various machine learning approaches (eg. supervised/unsupervised learning, deep learning etc.), and evaluate the performance of ML algorithms. 
• Proven ability to remain up-to-date with the latest advancements in Generative AI approaches (eg. OpenAI, LangChain, Stable Diffusion APIs).
• Experience developing, documenting, and supporting REST APIs
• A degree in Computer Science, Engineering, or a related field or equivalent practical experience.

Toast creates technology to help restaurants and local businesses succeed in a digital world, helping business owners operate, increase sales, engage customers, and keep employees happy.
 

As Senior Analyst in our Model Risk Management team, you will help manage the Model Risk Program including completing model validation reviews, maintaining the model risk inventory, and monitoring model performance particularly for Fraud and Gen AI Models. You will work closely with the Data Science Team, architects, engineers and product managers to assess the risk of model design, implementation, and use across product lines.

A day in the life (Responsibilities) 

• Support the implementation and day-to-day execution of the Second Line of Defense (2LOD) Model Risk Management (MRM) program for high-risk models, with particular focus on Fraud detection models (Transaction Fraud & Merchant Fraud) and Generative AI / LLM-based systems deployed across Toast.
• Assist in maintaining and enhancing the Model Risk Management framework, including policies, procedures, validation standards, governance documentation, templates, and best practices aligned with evolving regulatory and industry expectations.
• Enforce model lifecycle standards across development, implementation, use, monitoring, recalibration, change management, governance, and decommissioning, ensuring appropriate controls for traditional ML models as well as GenAI systems (e.g., RAG architectures, copilots, AI-assisted decision tools).
• Contribute to the development, risk-tiering, and ongoing maintenance of a comprehensive model inventory, including assessment of model impact, intrinsic risk (complexity and methodology), reliance on model outputs, and emerging AI-specific risks.
• Perform independent model validation reviews under the guidance of senior leadership, covering conceptual soundness, data integrity, model methodology, performance metrics (e.g., AUC, precision/recall, calibration), stability, bias/fairness risk, explainability, and monitoring frameworks. Produce validation reports and track issue remediation plans through closure.
• For Fraud models, evaluate class imbalance handling, threshold optimization, cost-sensitive performance metrics, operational overlays, rule-based controls, and portfolio-level impact analyses.
• For Generative AI systems, validate systems and evaluate risks related to hallucination, prompt injection, adversarial vulnerabilities, data privacy and leakage, model explainability limitations, bias, guardrails, output monitoring, jailbreak testing, regression testing, and human-in-the-loop controls.
• Partner with Data Science, Data Engineering, Product/Engineering, Information Security, Legal/Compliance, Finance, Credit Risk and Business teams to obtain documentation, perform effective challenge, conduct validation and oversee performance monitoring
• Prepare reports and executive materials summarizing model risk issues, validation findings, monitoring insights, and remediation status for leadership review, risk committees, audit committees, and internal audit engagements.
• Research and stay informed on industry developments in fraud analytics, machine learning, Generative AI governance, and regulatory guidance (e.g., SR 11-7, OCC 2011-12, NIST AI RMF). Propose enhancements to strengthen Toast’s Model Risk and AI Governance framework.
• Contribute to the development of model risk training materials and support delivery of training sessions to key stakeholders to enhance awareness of fraud model risk and AI-related risks.
• Support ad-hoc initiatives related to model risk governance, AI oversight, regulatory compliance, and enterprise risk management enhancements.

What you'll need to thrive (Requirements)

• Advanced degree in Data Science, Statistics, Applied Mathematics, Computer Science, Engineering, or a related quantitative discipline
• 5+ years of relevant industry experience in Model Risk Management, Model Validation, Data Science, or Machine Learning within fintech, banking, payments, technology, or consulting environments, with exposure to fraud analytics, credit risk, or AI/ML model governance.
• Strong understanding of machine learning methodologies and statistical foundations, including model development, validation techniques, performance evaluation, calibration, and stability analysis.
• Hands-on experience with fraud detection models (e.g., transaction monitoring, chargeback prediction, merchant risk scoring) and familiarity with concepts such as class imbalance handling, threshold optimization, precision/recall trade-offs, and cost-sensitive evaluation.
• Familiarity with Generative AI and LLM-based systems (e.g., RAG architectures, embeddings, prompt engineering, AI copilots) and awareness of associated risks such as hallucination, bias, prompt injection, and data leakage.
• Strong proficiency in Python and SQL; experience with data science and ML tools such as Spark, scikit-learn, XGBoost, LightGBM, TensorFlow, or PyTorch. Familiarity with software engineering best practices (version control, CI/CD, testing frameworks, Airflow, AWS or cloud platforms) is a plus.
• Knowledge of model risk management frameworks and regulatory guidance (e.g., SR 11-7, OCC 2011-12) and familiarity with emerging AI governance frameworks (e.g., NIST AI RMF) is highly desirable.
• Ability to translate complex quantitative methodologies into clear business insights and effectively challenge first-line model development teams while maintaining strong cross-functional partnerships.
• Demonstrated critical thinking, analytical rigor, and structured problem-solving skills, with the ability to manage multiple priorities and deliver high-quality outputs under tight deadlines.
• Excellent written and verbal communication skills, including experience drafting formal validation reports, executive summaries, and committee-level materials.

AI at Toast

At Toast, one of our company values is that we're hungry to build and learn. We believe learning new AI tools empowers us to build for our customers faster, more independently, and with higher quality. We provide these tools across all disciplines, from Engineering and Product to Sales and Support, and are inspired by how our Toasters are already driving real value with them. The people who thrive here are those who embrace changes that let us build more for our customers; it’s a core part of our culture.

Our Total Rewards Philosophy

We strive to provide competitive compensation and benefits programs that help to attract, retain, and motivate the best and brightest people in our industry. Our total rewards package goes beyond great earnings potential and provides the means to a healthy lifestyle with the flexibility to meet Toasters’ changing needs. Learn more about our benefits at https://careers.toasttab.com/toast-benefits.

What are we looking for?

SentinelOne is seeking a Software Engineer to join the Observo AI team in India, our cutting-edge AI-driven data pipeline optimization platform. This role will be responsible for developing and maintaining high-performance systems that process massive volumes of telemetry data while reducing costs and improving insights for enterprise customers.

We're looking for someone who errs on the side of simplicity, who has a passion for craftsmanship in code, and who believes deeply in the value of testing. You should be the kind of engineer who writes tests even when nobody is watching—because you understand that quality matters. We value engineers who enjoy performance tuning, extracting the last ounce of efficiency from systems, and who are excited about working with databases, distributed systems, and open source technologies.

This role is part of the Observo AI engineering organization and offers the opportunity to work on innovative technology that directly impacts enterprise data management at scale. This is a hybrid role with 3 days in our Bengaluru office.

What Will You Do?

• Develop and maintain scalable data processing pipelines that handle large volumes of telemetry data (logs, metrics, traces)
• Build and enhance ML-driven data routing, filtering, and transformation components to optimize customer data volumes while preserving critical insights
• Implement real-time analytics and monitoring features using modern software engineering practices
• Work with cloud-native microservices and APIs that integrate with major observability platforms (Splunk, Elastic, Datadog, New Relic)
• Contribute to monitoring, alerting, and observability solutions for distributed systems
• Write comprehensive tests for all code changes, ensuring reliability and maintainability
• Participate in code reviews, pair programming, and collaborative development practices
• Collaborate with senior engineers, Product, and DevOps teams to deliver customer-focused solutions
• Conduct performance and scale testing to optimize system efficiency
• Learn and apply emerging technologies in AI/ML, data engineering, and observability
• Contribute to technical documentation and knowledge sharing within the team

What Skills and Knowledge Should You Bring?

• 3+ years of software engineering experience with focus on backend development, distributed systems, or data processing
• Demonstrated commitment to code quality and testing practices throughout your career
• Experience that shows you care about the craft of software engineering
• Strong proficiency in Go, Java, Python, or similar programming languages with understanding of software engineering best practices
• Experience with cloud platforms (AWS, GCP, Azure) and containerization technologies (Docker, Kubernetes)
• Familiarity with data processing frameworks such as Apache Kafka, Apache Spark, or streaming technologies
• Basic understanding of database technologies including SQL (PostgreSQL, MySQL) and NoSQL (MongoDB, Redis) systems
• Understanding of data formats and protocols commonly used in enterprise systems (JSON, REST APIs, message queues)
• Experience with version control systems (Git) and CI/CD practices
• Strong belief in testing—you write tests even when you have the freedom to skip them
• Bias toward simplicity and maintainability in software design
• Interest in performance and scale testing; you enjoy tuning systems for maximum efficiency
• Passion for craftsmanship in code quality and attention to detail
• Commitment to continuous learning and improvement
• Good communication skills with ability to collaborate effectively in a team environment
• Experience with or interest in pair programming and extreme programming practices
• Fluency in English with good written and verbal communication skills
• Eagerness to learn from senior engineers and contribute to team success
• Bachelor's degree in Computer Science, Engineering, or related field from a recognized institution
• Exposure to functional programming languages (Haskell, Scala, Elixir, OCaml, F#)
• Exposure to systems programming languages (Rust, C++, C)
• Contributor to open source projects, particularly in databases, distributed systems, or observability
• Experience with machine learning concepts and frameworks (TensorFlow, PyTorch, scikit-learn)
• Knowledge of monitoring and observability tools such as Prometheus, Grafana, or ELK stack
• Personal projects demonstrating passion for databases, distributed systems, or performance optimization

Why Us? 

You will be joining a cutting-edge company, where you will tackle extraordinary challenges and work with the very best in the industry

• Flexible working hours and hybrid/remote work model.
• Flexible Time Off.
• Flexible Paid Sick Days.
• Global gender-neutral Parental Leave (16 weeks, beyond the leave provided by the local laws) 
• Generous employee stock plan in the form of RSUs (restricted stock units)
• On top of RSUs, you can benefit from our attractive ESPP (employee stock purchase plan)
• Gym membership/sports gears by Cultfit.
• Wellness Coach app, with 3,000+ on-demand sessions, daily interactive classes, audiobooks, and unlimited private coaching. 
• Private medical insurance plan for you and your family.
• Life Insurance covered by S1 (for employees)
• Telemedical app consultation (Practo)
• Global Employee Assistance Program (confidential counseling related to both personal and work life matters)
• High-end MacBook or Windows laptop.
• Home-office-setup allowances (one time) and maintenance allowance. 
• Internet allowances.
• Provident Fund and Gratuity (as per govt clause)
• NPS contribution (Employee contribution)
• Half yearly bonus program depending on the individual and company performance.
• Above standard referral bonus as per policy.
• Udemy Business platform for Hard/Soft skills Training & Support for your further educational activities/trainings
• Sodexo food coupons.

The Role

Lead the maturation of Securly's content classification system — building the ML infrastructure that determines, at scale, whether web content is appropriate for K-12 students, and establishing the rigorous evaluation framework that product and leadership teams depend on.

This is applied ML with direct student safety impact — not research. You will lead a significant uplift of Securly's classification models: refactoring binary models to proper multiclass classification, building labeled evaluation datasets, and producing standardized model cards with per-category precision, recall, F1, and confusion matrix analysis.

At L5, you are the technical leader of the data science function for content safety. You will define the evaluation methodology the team follows, set the standard for what a model card must contain before a model ships, mentor the team on applied ML rigor, and serve as the interface between data science and engineering on production integration constraints.

What It Means to Be L5 at Securly

L5 at Securly is a Staff Engineer. You are the technical owner, not just an implementer.

• Drive technical direction for your initiative end-to-end: from architecture to production, with minimal oversight from your engineering manager.
• Identify and resolve ambiguity in requirements, system boundaries, and design tradeoffs without waiting for a fully-formed spec.
• Mentor L3/L4 engineers on the team: code reviews, design feedback, pairing, and raising the bar for what production-quality work looks like.
• Partner with your L6 technical lead and the Distinguished Engineer on architectural decisions, surfacing tradeoffs clearly rather than deferring them upward.
• Contribute to cross-team engineering standards: you are expected to influence practices beyond your immediate squad.
• Translate technical context into clear written artifacts that non-engineers (PM, Support, Leadership) can act on.
• Participate in on-call rotation and own the full incident lifecycle for your system: detection, diagnosis, resolution, and retrospective.

What You'll Do

• Define the evaluation methodology for content classification at Securly: establish what a model card must contain and hold every model release to that standard before it ships.
• Lead the multiclass refactor of Securly's content classification models: redesign binary models to handle multi-label, multi-class content categories (Adult Content, Violence, Self-Harm, Social Media, and others).
• Build and maintain labeled evaluation datasets with robust annotation workflows; address class imbalance and label noise systematically; document dataset curation decisions in a versioned data card.
• Connect offline evaluation to production monitoring — surface classification drift and error patterns before they become customer-facing issues.
• Investigate and resolve misclassification errors: false positives (over-blocking) and false negatives (under-blocking); produce written root cause analyses.
• Build and maintain training data pipelines: ingestion, cleaning, labeling, and versioning at scale.
• Mentor the existing AI team on evaluation methodology, model development practices, and data science communication rigor.
• Communicate precision/recall tradeoffs to product managers and engineers; produce executive-level summaries of classification quality for leadership.
• Collaborate with engineering to integrate model outputs into the production filtering stack with appropriate latency and reliability constraints.
• Research and prototype improvements: feature representations, model architectures, active learning for label efficiency, domain adaptation for emerging content categories.

Skills & Requirements

Who You Are

• You have shipped ML models to production and lived with the consequences — you know what model drift looks like and how to catch it before it becomes a customer issue.
• You treat evaluation as a first-class engineering artifact. A model without a model card is not finished — and you set and enforce that standard for the team.
• You define the methodology, not just apply it. You produce the evaluation framework that other data scientists use, and you hold them to it.
• You can communicate precision/recall tradeoffs to a product manager and to a senior engineer in the same conversation, calibrated to each audience.
• You are energized by problems with real stakes: a false negative in Self-Harm classification is not an acceptable error rate.
• You mentor by example and by expectation: your code, your analysis, and your documentation set the standard.

About Securly

Benefits

The Role

The Senior Data Scientist will lead the maturation of Securly's content classification system — building the ML infrastructure that determines, at scale, whether web content is appropriate for K-12 students, and establishing the rigorous evaluation framework that product and leadership teams depend on.

This is applied ML with direct student safety impact — not research. You will lead a significant uplift of Securly's classification models: refactoring binary models to proper multiclass classification, building labeled evaluation datasets, and producing standardized model cards with per-category precision, recall, F1, and confusion matrix analysis.

At L5, you are the technical leader of the data science function for content safety. You will define the evaluation methodology the team follows, set the standard for what a model card must contain before a model ships, mentor the team on applied ML rigor, and serve as the interface between data science and engineering on production integration constraints.

What It Means to Be L5 at Securly

L5 at Securly is a Staff Engineer. You are the technical owner, not just an implementer.

• Drive technical direction for your initiative end-to-end: from architecture to production, with minimal oversight from your engineering manager.
• Identify and resolve ambiguity in requirements, system boundaries, and design tradeoffs without waiting for a fully-formed spec.
• Mentor L3/L4 engineers on the team: code reviews, design feedback, pairing, and raising the bar for what production-quality work looks like.
• Partner with your L6 technical lead and the Distinguished Engineer on architectural decisions, surfacing tradeoffs clearly rather than deferring them upward.
• Contribute to cross-team engineering standards: you are expected to influence practices beyond your immediate squad.
• Translate technical context into clear written artifacts that non-engineers (PM, Support, Leadership) can act on.
• Participate in on-call rotation and own the full incident lifecycle for your system: detection, diagnosis, resolution, and retrospective.

What You'll Do

• Define the evaluation methodology for content classification at Securly: establish what a model card must contain and hold every model release to that standard before it ships.
• Lead the multiclass refactor of Securly's content classification models: redesign binary models to handle multi-label, multi-class content categories (Adult Content, Violence, Self-Harm, Social Media, and others).
• Build and maintain labeled evaluation datasets with robust annotation workflows; address class imbalance and label noise systematically; document dataset curation decisions in a versioned data card.
• Connect offline evaluation to production monitoring — surface classification drift and error patterns before they become customer-facing issues.
• Investigate and resolve misclassification errors: false positives (over-blocking) and false negatives (under-blocking); produce written root cause analyses.
• Build and maintain training data pipelines: ingestion, cleaning, labeling, and versioning at scale.
• Mentor the existing AI team on evaluation methodology, model development practices, and data science communication rigor.
• Communicate precision/recall tradeoffs to product managers and engineers; produce executive-level summaries of classification quality for leadership.
• Collaborate with engineering to integrate model outputs into the production filtering stack with appropriate latency and reliability constraints.
• Research and prototype improvements: feature representations, model architectures, active learning for label efficiency, domain adaptation for emerging content categories.

Skills & Requirements

Who You Are

• You have shipped ML models to production and lived with the consequences — you know what model drift looks like and how to catch it before it becomes a customer issue.
• You treat evaluation as a first-class engineering artifact. A model without a model card is not finished — and you set and enforce that standard for the team.
• You define the methodology, not just apply it. You produce the evaluation framework that other data scientists use, and you hold them to it.
• You can communicate precision/recall tradeoffs to a product manager and to a senior engineer in the same conversation, calibrated to each audience.
• You are energized by problems with real stakes: a false negative in Self-Harm classification is not an acceptable error rate.
• You mentor by example and by expectation: your code, your analysis, and your documentation set the standard.

About Securly

Benefits

Rhombus Power India is purposefully transforming the nation’s defense and national security enterprises with Guardian, its Artificial Intelligence platform for strategic, operational, and tactical decision-making at the speed of relevance.

We are looking for people who are driven by a sense of purpose. In this role, you will serve as a Data Engineer to solve our customer’s uniquely complex problems. We expect you to be a systems-level thinker and a real doer. You will excel in this role if you are hungry to make a difference and are intellectually bold. And we sure hope that you smile when you hear our clients say, “If we can dream it, Rhombus can do it.”

Come join our cross-disciplinary and world-class team of technologists who are working hard every day to deliver game-changing solutions to transform national security.

Location

New Delhi, India

Job Description

Rhombus’ Data Engineers are instrumental in designing and implementing data engineering activities on topical, mission-driven projects that inform our national security agenda. They analyze, build, and maintain our organization’s data infrastructure and processing systems. As a Data Engineer, you’ll perform various code development and query needs for integration with new and existing applications, dashboards and machine learning pipelines. You’ll work cross functionally with other departments and utilize your skills at all stages of the analytics pipeline to create results that drive business values and customer success! You’ll be asked to travel to client sites where you’ll engage and collaborate directly with the client to discuss data pipelines, solutioning, and to ensure a strong client connection.

Responsibilities:

• Develop code using various programming and scripting languages to automate data ingestion and improve data management processes.
• Architect data repositories, stand up data platforms and develop data pipelines for ingestion, transformation, and aggregation.
• Review existing architecture, data strategy, and improve processes for data governance, data quality, and metadata management.
• Extract and analyze raw data from multiple data sources via APIs, SQL Stored Procedures, or Python scripts.
• Ability to develop scripts and programs for converting various types of data into usable formats and support project team to scale, monitor and operate data platforms.
• Collaborate with a multi-disciplinary team of analysts, data scientists, data engineers, developers, and data consumers in a fast-paced, agile environment.
• You’ll use your experience in analytical exploration and data examination while you manage the assessment, design, building, and maintenance of scalable platforms for clients.
• Communicate project status and results to various levels of leadership.

Qualifications:

• A Bachelor’s degree in Data Analytics, Computer Science, Computer Engineering, Information Systems/Sciences, or other relevant area (or equivalent experience) and at least 1 year of professional experience, or a Master’s degree with strong academic project experience.
• Experience with 1 or more programming and scripting languages, with a strong focus on Python, Pandas and Numpy. Other languages include: Shell, PERL, Java, C/C++/C#, Scala, etc.
• Experience with 1 or more of the following relational, noSQL and/or file based storage (e.g. MYSQL, MongoDB, SQL Server, Oracle, Postgres, Hbase, DynamoDB, etc.)
• Experience building and maintaining ETL data pipelines
• Experience with software development life cycle including testing, documenting, delivery and support
• Working knowledge of AWS/cloud technologies
• Experience using query optimization as well as data modeling techniques.
• Familiarity with machine learning frameworks (such as TensorFlow, Scikit-Learn, etc.)

Personal Qualities:

• Ability to contextualize data as it relates to Rhombus’ vision. We want someone who can understand the “why” and “so what”, and not just the “how”. Our Data Engineers help us transmit the enthusiasm we have around the data work to the individuals doing that work.
• Must have strong problem-solving skills and demonstrated excellent oral and written communication skills.
• We’re seeking folks with strong intellectual curiosity and creativity, with an ability and willingness to learn new skills and apply novel solutions to problems.
• Comfort in a fast-paced start-up environment is crucial, with the ability to consistently revise your approach in response to new information, and to be flexible and adaptive.

At Reltio®, we believe data should fuel business success. Reltio’s AI-powered data unification and management capabilities—encompassing entity resolution, multi-domain master data management (MDM), and data products—transform siloed data from disparate sources into unified, trusted, and interoperable data. Reltio Data Cloud™ delivers interoperable data where and when it's needed, empowering data and analytics leaders with unparalleled business responsiveness. Leading enterprise brands—across multiple industries around the globe—rely on our award-winning data unification and cloud-native MDM capabilities to improve efficiency, manage risk and drive growth.

At Reltio, our values guide everything we do. With an unyielding commitment to prioritizing our “Customer First”, we strive to ensure their success. We embrace our differences and are “Better Together” as One Reltio. We are always looking to “Simplify and Share” our knowledge when we collaborate to remove obstacles for each other. We hold ourselves accountable for our actions and outcomes and strive for excellence. We “Own It”. Every day, we innovate and evolve, so that today is “Always Better Than Yesterday”. If you share and embody these values, we invite you to join our team at Reltio and contribute to our mission of excellence.

Reltio has earned numerous awards and top rankings for our technology, our culture and our people. Reltio was founded on a distributed workforce and offers flexible work arrangements to help our people manage their personal and professional lives. If you’re ready to work on unrivaled technology where your desire to be part of a collaborative team is met with a laser-focused mission to enable digital transformation with connected data, let’s talk!

About the Role

We are seeking a Senior AI Engineer with a strong foundation in Python capabilities, and hands-on experience building Agentic AI applications that integrate with Large Language Models (LLMs) Large Language Models (LLMs). We are also looking for him to be a full-stack Engineer with hands-on experience with mobile front-end hands-on experience with mobile front-end Flutter, React-native. This role blends traditional backend engineering expertise with next-generation AI agentic systems development, requiring not just system design skills, but also creativity in prompt engineering, AI product development and working with data-rich environments.

You will contribute to the design and implementation of intelligent backend services that coordinate LLMs, agents, and data workflows to support enterprise-grade agentic systems.

Key Responsibilities

• Develop robust, scalable Java/Python based backend systems that enable the orchestration of Agentic AI workflows.
• Develop state-of-the-art AI/ML models for solving real-world data management challenges such as entity resolution, classification, similarity matching, and anomaly detection.
• Integrate LLMs (e.g., OpenAI, Mistral, Claude, LLaMA) into backend pipelines to power autonomous or semi-autonomous decision-making.
• Hands on experience with mobile front-end Flutter, React-native etc.
• Develop scalable ML workflows using Spark, MLlib, PyTorch, TensorFlow, or MLFlow, with seamless integration into production systems.
• Translate business needs into technical design and collaborate with data scientists, product managers, and platform engineers to operationalize models.
• Work closely with various stakeholders to design agent architectures and LLM toolchains (using frameworks like LangGraph, Crew AI, AutoGen, etc.).
• Implement services and APIs that manage prompt chaining, tool invocation, and contextual memory for agents.
• Collaborate with data engineers to ensure clean, efficient, and real-time access to structured and semi-structured data.
• Apply prompt engineering best practices to improve agent behavior, task accuracy, and adaptability.
• Monitor and optimize service performance, reliability, and scalability in production environments.
• Continuously monitor and improve model performance using feedback loops, A/B testing, drift detection, and retraining strategies.
• Contribute to code reviews, mentoring, and best practices for hybrid backend/AI development.

Required Qualifications

• 5+ years of overall experience mobile front-end Flutter, React-native etc
• 2+ years of experience in developing and deploying machine learning models and AI products in production environments.
• Experience in Agentic AI systems development using tools such as LangGraph, Crew AI, AutoGen, or similar.
• Proficiency in Python (NumPy, scikit-learn, pandas, PyTorch/TensorFlow) and experience with large-scale data processing tools (Spark, Kafka, Airflow).
• Experience integrating or orchestrating LLMs within business workflows or intelligent assistants.
• Solid understanding of prompt engineering techniques (e.g., system messages, chaining, tool invocation prompts).
• Familiarity with data engineering concepts, including pipelines, data models, and ETL workflows.
• Strong grasp of object-oriented design, data structures, and algorithms.

Preferred Qualifications

• Experience with LLM orchestration frameworks (e.g., LangChain, LlamaIndex, RAG pipelines).
• Background in building microservices or backend systems for data-rich AI/ML platforms.
• Experience with vector databases, embedding services, or semantic search integration.
• Knowledge of cloud platforms (AWS, GCP, or Azure), containerization (Docker), and DevOps best practices.
• Experience in developing LLM-powered agents, copilots, or task bots.

What We Offer

• Opportunity to work on cutting-edge backend and AI systems, including agentic automation and LLM innovation.
• A flexible hybrid work model in our Bangalore office.
• Competitive compensation with performance-based rewards.
• A culture that promotes engineering excellence, experimentation, and growth.Access to learning platforms, technical workshops, and industry-leading AI research.

Why Join Reltio?*

• Health & Wellness:
  • Comprehensive Group medical insurance including your parents with additional top-up options.
  • Accidental Insurance
  • Life insurance
  • Free online unlimited doctor consultations
  • An Employee Assistance Program (EAP)
• Work-Life Balance:
  • 36 annual leaves, which includes Sick leaves – 18, Earned Leaves - 18
  • 26 weeks of maternity leave, 15 days of paternity leave
  • Very unique to Reltio - 01 week of additional off as recharge week every year globally
• Support for home office setup:
  • Home office setup allowance.
• Stay Connected, Work Flexibly: Mobile & Internet Reimbursement
• No need to pack a lunch—we’ve got you covered with a free meal.And many more…..

Role: GenAI Lead Engineer

Experience: 8+ years total (with significant hands-on GenAI / LLM work)

Job Overview:

We are seeking an innovative and highly skilled Lead Generative AI (GenAI) Engineer to spearhead the design, development, and deployment of advanced AI-powered solutions. In this role, you will lead a team of engineers and data scientists to harness cutting-edge Generative AI technologies and implement them to solve complex business problems, enhance user experiences, and drive innovation. This role combines deep technical expertise, leadership, and a strong understanding of AI trends and tools.

Key Responsibilities:

• Technical Leadership:
• Lead the end-to-end design and implementation of Generative AI solutions.
• Provide technical guidance and mentorship to engineers and data scientists working on GenAI projects.
• Stay updated with the latest trends, research, and advancements in Generative AI and Large Language Models (LLMs).
• Solution Development:
• Architect, train, and fine-tune state-of-the-art LLMs and generative AI models
• Develop and optimize pipelines for prompt engineering, retrieval-augmented generation (RAG), and domain-specific fine-tuning.
• Develop and deploy generative AI models, particularly focusing on ChatGPT, using Python on Azure or AWS Platform or .Net on Azure platform
• Ensure scalability, performance, and security of AI solutions deployed in production.
• Integration and Deployment:
• API Development: Ability to define and deliver API access for GenAI services, facilitating integration with other systems and applications.
• Collaborate with software engineering teams to integrate GenAI solutions into enterprise applications and services.
• Utilize cloud platforms (e.g., Azure, AWS, or GCP) to deploy and manage AI models and APIs.
• Leverage MLOps practices for continuous model monitoring, retraining, and improvement.
• Data Strategy and Preparation:
• Collaborate with data engineering teams to ensure high-quality data acquisition, preprocessing, and augmentation for model training and fine-tuning.
• Implement data governance and privacy practices in line with organizational policies.
• Innovation and Research:
• Experiment with new generative AI techniques, such as multimodal AI, reinforcement learning with human feedback (RLHF), and active learning.
• Evaluate and recommend AI frameworks, libraries, and platforms for project requirements.
• Stakeholder Collaboration:
• Work closely with product managers, business stakeholders, and UX designers to define AI-powered product features and use cases.
• Present technical concepts, project progress, and AI capabilities to non-technical audiences.

Key Requirements

• Technical Skills:
• Hands-on experience with cloud platforms and services for AI/ML, such as Azure AI Services, Azure Machine Learning, AWS Bedrock, or Google Vertex AI.
• Hands on experience in any of LLMs such as OpenAI’s ChatGPT Models , Gemini, Llama 2 ,Claude 2 ,Grok
• Hands on experience in any of the agentic frameworks like LangChain, Semantic kernel, AutoGen, CrewAi
• Hands on experience using any of vector database like Chroma, Pinecone, Weaviate, Faiss
• Experience with multimodal AI and advanced techniques like Tree-of-Thoughts, Retrieval-Augmented Generation (RAG), or Reinforcement Learning with Human Feedback (RLHF)
• Strong expertise in LLMs and generative AI frameworks like OpenAI, Hugging Face Transformers, or similar platforms.
• Deep understanding of natural language processing (NLP) concepts, including tokenization, embeddings, and sequence-to-sequence models.
• Proficiency in Python and libraries such as TensorFlow, PyTorch, and Scikit-learn.
• Experience in CI/CD pipeline management and automation tools, particularly within the Azure DevOps environment. Knowledge of containerization (e.g., Docker) and orchestration tools is also important
• Familiarity with MLOps tools and practices, such as MLflow, Kubeflow, or Docker.

Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field (Ph.D. preferred).
• 8+ years of experience in AI/ML engineering, with 2+ years specifically in Generative AI.
• Minimum of 2 years of experience in building Conversational AI applications using cloud-based services and in orchestrating AI/ML services for building a complete solution
• Minimum of 6 years of extensive full-time experience in Data Analysis, Statistics, Machine Learning, or Computer Science
• Proven track record of leading AI projects from inception to production.
• Experience with multimodal AI and advanced techniques like Tree-of-Thoughts, Retrieval-Augmented Generation (RAG), or Reinforcement Learning with Human Feedback (RLHF).
• Certifications in AI/ML or cloud platforms (e.g., Azure AI Engineer, AWS Certified Machine Learning).

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 

Role Summary

We are looking for a technically strong AI / ML Developer with hands-on expertise in training and fine-tuning Small Language Models (SLMs) and RAG Solutions. The ideal candidate will drive end-to-end AI Solutions — from dataset curation and pre-processing to training, evaluation, and production deployment. You will collaborate closely with product, product engineers, and infrastructure teams to build AI solutions that are efficient, scalable, and business-aligned.

Key Responsibilities

1  Model Design & Training

• Design, train, and fine-tune Small Language Models (SLMs) using frameworks such as PyTorch, TensorFlow, or JAX.
• Conduct experiments with supervised fine-tuning (SFT), reinforcement learning from human feedback (RLHF), and instruction tuning.
• Implement efficient training pipelines leveraging distributed training (DDP, FSDP) across GPU/TPU clusters.
• Perform hyperparameter optimisation, ablation studies, and model selection based on benchmark results.
• Develop and maintain data pipelines for collecting, cleaning, tokenising, and pre-processing large-scale training corpora.

2  Model Evaluation & Quality

• Define and implement evaluation frameworks including perplexity, BLEU, ROUGE, BERTScore, and task-specific benchmarks.
• Conduct red-teaming, bias analysis, and safety evaluations to ensure responsible AI deployment.
• Benchmark models against established baselines (e.g., GPT-2, Phi, Mistral) and track performance over iterations.
• Collaborate with QA teams to build regression suites for model versioning and continuous evaluation.

3  MLOps & Deployment

• Containerise and deploy models using Docker, Kubernetes, and cloud-native ML platforms (AWS SageMaker / GCP Vertex AI / Azure ML).
• Build and maintain model registries, experiment tracking (MLflow, Comet), and reproducible training pipelines.
• Optimise inference performance through quantisation (INT8, INT4), pruning, distillation, and ONNX/TensorRT conversion.
• Monitor model drift, data drift, and performance degradation in production; implement automated retraining triggers.

4  Research & Innovation

• Stay current with state-of-the-art NLP/LLM research; prototype and validate new techniques from published literature.
• Contribute to internal knowledge sharing, technical documentation, and model cards.
• Explore parameter-efficient fine-tuning (PEFT) methods such as LoRA, QLoRA, and Adapter layers.
• Investigate and apply mixture-of-experts (MoE), retrieval-augmented generation (RAG), and agentic workflows as needed.

5  Collaboration & Stakeholder Management

• Work with product managers and domain experts to translate business requirements into model objectives and KPIs.
• Communicate model capabilities, limitations, and trade-offs clearly to both technical and non-technical stakeholders.
• Participate in architecture reviews, sprint planning, and cross-functional design discussions.

Required Qualifications

1  Education

• Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, Statistics, or a related quantitative field.
• Equivalent professional experience with a strong portfolio of delivered AI/ML projects will be considered.

2  Experience

• 4 – 6 years of professional experience in machine learning or NLP engineering.
• Minimum 2 years of direct, hands-on experience in training or fine-tuning language models (LLMs or SLMs).
• Demonstrable experience taking a model from dataset preparation through to production deployment.

3  Technical Skills — Core

• Programming: Python (proficient); familiarity with C++/CUDA a plus.
• Deep Learning Frameworks: PyTorch (primary), TensorFlow or JAX.
• NLP Libraries: Hugging Face Transformers, Datasets, PEFT, TRL, Accelerate.
• Training Infrastructure: Multi-GPU training, FSDP, DeepSpeed ZeRO stages 1–3.
• Data Engineering: Pandas, NumPy, Apache Spark or Dask for large-scale data prep.
• Vector DBs & Retrieval: FAISS, Pinecone, Weaviate, or equivalent.
• Cloud Platforms: AWS, GCP, or Azure — ML-specific services (SageMaker, Vertex AI, etc.).
• Version Control & CI/CD: Git, GitHub/GitLab, MLflow or W&B for experiment tracking.

4  Technical Skills — Nice to Have

• Experience with multimodal models or vision-language models (VLMs).
• Knowledge of model safety, alignment techniques, and responsible AI frameworks.
• Familiarity with LangChain, LlamaIndex, or similar orchestration frameworks.
• Contributions to open-source ML projects or publications at NeurIPS, ICML, EMNLP, ACL.

Behavioural Competencies

• Intellectual Curiosity: Keeps up with rapidly evolving AI research and applies learnings pragmatically.
• Problem Solving: Approaches ambiguous problems with structured, data-driven thinking.
• Ownership: Takes full accountability for model quality, timelines, and production reliability.
• Collaboration: Works effectively in cross-functional teams with diverse skill sets.
• Communication: Distils complex technical concepts for diverse audiences.
• Adaptability: Thrives in a fast-paced environment where priorities evolve with research breakthroughs.

About the Opportunity

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.

 

 

 

Learn more about us

 

 

 

• 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.

 

 

Equal Opportunity

Cognite is committed to creating a diverse and inclusive environment at work and is proud to be an equal opportunity employer. All qualified applicants will receive the same level of consideration for employment.

Job Title: Manager, Software Engineer

Locations: Bangalore

Reports to: VP, AI Engineering

 A quick snapshot…

Conga is looking to hire a Manager, Software Engineering to join our extremely talented AI Engineering team. As an Engineering Manager at Conga, you’ll lead a team of software engineers working on our next generation AI Solutions. This team will be responsible for building statistical and machine learning models that support product features across the company. You’ll get to work directly with other Engineering Managers, Architects, Data Scientists, Product Managers, and Directors, all of whom make up the larger team. In this highly collaborative environment, you will have the opportunity to grow as a leader and help mentor others.

This position requires experience leading software engineering initiatives, knowledge of AI/ML solutions, as well as excellent people and time management skills. This role will be reporting to the VP of AI Engineering and will be a key engineering leader inside the Conga AI Pillar. The role requires you to collaborate with other leaders at Conga and guide your team to deliver high quality software solutions in a timely manner. The ideal candidate for this position is passionate about people, process, technology, and delivering customer values.

Conga works in an agile environment where there are daily stand-ups, code reviews, and constant communication within each self-managed cross-functional team. The ability to communicate effectively with other Engineering and Product leaders, as well as work closely with other your team members are key components for success in this position.

Why it’s a big deal…  

8+ or more years of experience in the Software Engineering industry with a record of increasing responsibility leading software development initiatives, and 3+ years managing teams.

Deep understanding of the Software Development Lifecycle (SDLC) and Machine Learning Lifecycle (MLL).

Lead and drive the strategy, vision and roadmap for building robust, scalable AI/ML foundations and platforms — including but not limited to:

•  Feature stores
• Distributed ML model training
• Model versioning and evaluation
• Monitoring, drift detection, and automated retraining pipelines
• Responsible AI, model explainability, and fairness assessments

Experience with productionizing ML models and integrating them into real-time and batch applications. Work closely with data science partners and domain engineering teams to understand AI/ML use cases and build corresponding foundations for personalization, NLP, forecasting, recommendations, and generative AI.

Experience using a popular programming language such as: Python (preferred), Java, C#, Scala, etc.

Solid understanding of modern software development practices including object-oriented programming, concurrency, design patterns, microservices architecture, RESTful API design, and test-driven development.

Experience with software testing concepts and tools: white/black box testing, coverage analysis, mocking, PyTest/xUnit, Selenium, etc.

Hands-on experience with GCP technologies such as BigQuery, GKE, GCS, DataFlow, Kubeflow, and Vertex AI — or equivalent services in AWS and/or Azure.

Familiarity with ML frameworks and tools such as TensorFlow, PyTorch, MLflow, scikit-learn, HuggingFace Transformers, etc.

Strong experience with Infrastructure-as-Code and CI/CD tools used to automate deployment to cloud platforms: Terraform, GitHub Actions, Concourse, Ansible, etc.

Excellent leadership, decision-making, and communication skills, with the ability to translate business needs into engineering outcomes.

Experience with AI product lifecycle management, including experimentation tracking, model governance, and release management.

Experience with Python is ideal; Java/Spring is a strong plus.

Education: Bachelor’s degree in computer science, Engineering, or a related technical field; Master’s degree preferred 

Are you the person we’re looking for?  

Provide engineering leadership and mentorship to a team of software engineers.

Be a strong engineering leader responsible for executing the Conga AI roadmap using agile practice.

Experience implementing scalable data and AI/ML solutions in a product-driven technology environment.

Manage, lead, and motivate cross-functional, interdisciplinary teams of software engineers to achieve strategic and tactical business outcomes.

Mentor and grow engineers in your team, fostering a culture of teamwork, accountability, and continuous improvement.

Demonstrated ability to skillfully hire, coach, and performance manage a team of technology professionals.

Partner with others at Conga to ensure engineering tasks are understood, broken down, and implemented to the highest of quality standards.

Collaborate with members of the team to solve challenging engineering tasks on time and with high quality.

Encourage skill growth of your team members.

Assist and adhere to enforcement of project deadlines and schedules.

Actively communicate with team members to clarify requirements and overcome obstacles to meet the team goals.

Highly technical, confident at the operational management level and comfortable in an engineering-heavy organization.

Track record of being a strong leader, with the ability to influence across teams and levels.

Work with development teams in an agile context as it relates to software development.

Here’s what will give you an edge…

Provide architectural guidance and technical oversight for AI/ML systems, ensuring solutions are scalable, secure, and production ready.

Drive engineering excellence by championing robust design, peer reviews, and efficient CI/CD practices tailored for AI systems.

Foster strong cross-functional partnerships with Product, Data Science, ML-Ops, and DevOps teams to accelerate delivery and innovation.

Travel Requirement

Limited travel to other company offices upon request

#LI-UB1

Job Title: Senior Full Stack Machine Learning Engineer

About Us:

Inovalon is a leading healthcare technology company dedicated to revolutionizing the healthcare industry through innovative AI and machine learning solutions. Our mission is to leverage cutting-edge technology to improve health outcomes and streamline healthcare processes. We are looking for a talented and experienced Senior Full Stack Machine Learning Engineer to join our dynamic team.

Job Description:

• As a Senior Full Stack Machine Learning Engineer, you will play a pivotal role in designing, developing, and deploying machine learning models that drive our healthcare solutions. You will work closely with data scientists, software engineers, and product managers to build scalable and robust machine learning systems. Your expertise will help us transform healthcare data into actionable insights, ultimately improving patient care and operational efficiency.

Key Responsibilities:

• Model Development: Design, implement, and optimize machine learning models for various healthcare applications, including predictive analytics, natural language processing, and generative AI.
• End-to-End Deployment: Develop and maintain the full lifecycle of machine learning solutions, from data preprocessing and model training to deployment and monitoring in production environments.
• Data Engineering: Collaborate with data engineers to build and maintain data pipelines, ensuring the availability of high-quality data for training and inference.
• Software Development: Write clean, efficient, and maintainable code for machine learning applications, ensuring seamless integration with existing systems.
• Performance Optimization: Continuously monitor and improve the performance of machine learning models and systems, addressing issues related to scalability, latency, and accuracy.
• Collaboration: Work closely with cross-functional teams to understand business requirements and translate them into technical solutions.
• Mentorship: Provide guidance and mentorship to junior engineers, fostering a culture of continuous learning and innovation.

Qualifications:

• Education: Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or a related field. Ph.D. is a plus.
• Experience: Minimum of 5 years of experience in machine learning, with a proven track record of deploying models in production environments.

Technical Skills:

• Proficiency in Python and relevant ML libraries (e.g., TensorFlow, PyTorch, scikit-learn).
• Proficiency in building applications leveraging generative AI technologies which includes LLM’s, prompt engineering, Vector Databases, RAG architectures and transfer learning is a plus.
• Experience with cloud platforms (e.g., AWS, GCP, Azure) and containerization technologies (e.g., Docker, Kubernetes).
• Strong knowledge of data structures, algorithms, and software engineering best practices.
• Familiarity with big data technologies (e.g., Hadoop, Spark) and data pipeline tools (e.g., Airflow, Kafka).
• Experience with frontend and backend development, including frameworks such as React, Node.js, and Django.

Domain Knowledge: Understanding of healthcare data standards (e.g., HL7, FHIR) and regulations (e.g., HIPAA) is a plus.

Soft Skills:

• Excellent problem-solving and analytical skills.
• Strong communication and collaboration abilities.
• Ability to work independently and as part of a team in a fast-paced environment.

What We Offer:

• Competitive salary and benefits package.
• Opportunity to work on impactful projects that improve healthcare outcomes.
• Collaborative and innovative work environment.
• Professional development and growth opportunities.
• Flexible work arrangements, including hybrid and remote options.

Join us in our mission to transform healthcare through technology! We look forward to hearing from you.

WHO YOU ARE

You are a passionate Python and AI/ML Engineer minimum 4 years of hands-on experience building intelligent systems. You thrive in fast-paced environments, love solving complex problems with data and algorithms, and take pride in delivering AI solutions that create real business impact. You have experience with cutting-edge Generative AI, scalable ML pipelines, and production-grade systems and you're energized by working at the frontier of what AI can do.

WHAT YOU'LL DO

1. Design, develop, and deploy machine learning models and Generative AI solutions — including classification, clustering, summarization, search & ranking, and information extraction.
2. Own end-to-end ML pipelines — from data ingestion and preprocessing through model training, deployment, and production monitoring.
3. Collaborate with cross-functional teams to translate business requirements into AI-driven features — applying NLP, outlier detection, and deep learning techniques where applicable.
4. Build robust, scalable, and well-documented Python-based RESTful APIs to expose ML models and AI services in production environments.
5. Optimize database interactions and ensure efficient data storage and retrieval for AI applications across SQL and NoSQL systems.
6. Stay current with the latest advances in AI/ML — integrating emerging approaches such as RAG pipelines, LLM fine-tuning, and vector search into live products.

WHAT YOU'LL NEED 

Python
Strong hands-on proficiency for building, scripting, and deploying AI/ML systems.
NumPy · Pandas · FastAPI · Scikit-learn
Machine Learning
Applied expertise across supervised, unsupervised, and deep learning — classification, clustering, outlier detection.
PyTorch · TensorFlow · XGBoost · DBSCAN

Generative AI (2+ yrs)
Hands-on experience building with LLMs — prompt engineering, RAG pipelines, summarization, and AI-powered features.
LLMs · RAG · Prompt Eng. · Fine-tuning

NLP & Search / Ranking
Processes language and builds relevance engines — NER, embeddings, semantic search, and ranking models.
spaCy · BERT · FAISS · Elasticsearch

API Development
Designs and ships secure, well-documented RESTful APIs exposing ML models as production-ready services.
REST · FastAPI · OAuth2 · Swagger

Databases
Proficient in SQL and NoSQL stores for structured and unstructured data pipelines supporting AI workloads.
PostgreSQL · MongoDB · Vector DBs

GOOD TO HAVE

Cloud Platforms
Deploys and scales AI workloads on AWS, Azure, or GCP.
AWS · Azure

TypeScript / JavaScript
Frontend or full-stack exposure for building ML-powered product interfaces.
TypeScript · React · Node.js

MLOps
Manages the ML lifecycle — tracking, versioning, and pipeline automation.
MLflow · Kubeflow · CI/CD

Containerization & Orchestration
Packages and scales AI services using containers and cluster management.
Docker · Kubernetes

About Truveta 

Truveta provides unprecedented real-world data and real-time intelligence, powered by a dataset built with and owned by US health systems united in a mission of Saving Lives with Data. Together, we power breakthrough medical discoveries, accelerate regulatory-grade evidence, and improve patient care. Today, Truveta enables research on more than 130 million de-identified patients across the US.   

Achieving Truveta’s ambitious mission requires an incredible team of talented and inspired people with a special combination of health, software and big data experience who share our company values.  

The Role 

We are seeking a highly motivated Postdoctoral Researcher to explore and develop novel applications of cutting-edge AI/ML technologies on large-scale real-world clinical data. 

This role is designed for recent PhD graduates who are passionate about pushing the boundaries of machine learning in healthcare. You will work at the intersection of machine learning, clinical data, and biomedical science, identifying new opportunities where modern AI can unlock insights that were previously out of reach. 

A key expectation is not just execution—but imagination: the ability to envision and prototype entirely new ways to use rich patient data to solve meaningful healthcare problems. 

What You’ll Do 

• Innovate: Identify and propose novel, high-impact applications of AI/ML using large-scale EHR data 

• Research & Prototype: Design, develop, and evaluate state-of-the-art models (e.g., foundation models, multimodal learning, causal ML, generative AI) 

• Work Across Modalities: Integrate structured and unstructured EHR data with emerging data types such as genomics, imaging, and clinical notes 

• Collaborate Cross-Functionally: Partner with clinicians, data scientists, and product teams to translate research ideas into real-world solutions 

• Publish & Share: Contribute to top-tier conferences/journals and represent Truveta in the research community 

• Explore the Unknown: Proactively identify problems that have not yet been addressed and define new research directions 

What We’re Looking For 

Minimum Qualifications 

• PhD in Computer Science, Machine Learning, Biomedical Informatics, or a related field 

• Strong background in machine learning, deep learning, or statistical modeling 

• Experience applying ML to healthcare, biomedical, or clinical datasets 

• Proficiency in Python and modern ML frameworks (e.g., PyTorch, TensorFlow) 

Preferred Qualifications 

• Experience with healthcare data (EHRs, claims, clinical notes) or biomedical data (genomics, imaging) 

• Familiarity with cutting-edge areas such as:  

• Foundation models / LLMs in healthcare 

• Multimodal learning 

• Causal inference 

• Representation learning on longitudinal data 

• Track record of publications in top-tier ML or healthcare venues (e.g., NeurIPS, ICML, ICLR, MLHC, AMIA) 

• Ability to work across disciplines and communicate with both technical and clinical stakeholders 

Who You Are 

• Curious and imaginative: You naturally think beyond existing solutions and ask “what hasn’t been done yet?” 

• Impact-driven: You care about applying research to real-world healthcare problems 

• Comfortable with ambiguity: You thrive in open-ended environments where defining the problem is part of the job 

• Collaborative: You enjoy working across domains and learning from experts in different fields 

Why This Role is Unique 

• Access to one of the largest and richest longitudinal EHR datasets in the US 

• Opportunity to work on previously infeasible problems at the intersection of AI and medicine 

• A balance of academic-style research freedom and real-world impact 

• Collaboration with leading healthcare systems and industry partners 

Example Problem Areas (Illustrative) 

• Learning patient trajectories using foundation models for clinical decision support 

• Discovering novel phenotypes or disease subtypes from multimodal data 

• Predicting treatment effectiveness using causal ML on real-world data 

• Generating synthetic cohorts for rare disease research 

• Integrating genomics + EHR for precision medicine applications 

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. 

About Us:

Inovalon is a leading healthcare technology company dedicated to revolutionizing the healthcare industry through innovative AI and machine learning solutions. Our mission is to leverage cutting-edge technology to improve health outcomes and streamline healthcare processes.

Role overview

 As an MLOps Engineer, you will design, build, and operate the infrastructure and tooling that power end-to-end ML workflows on AWS, including SageMaker, Bedrock, and Snowflake Cortex. You will partner closely with data scientists, ML engineers, and platform teams to ensure models are reliable, secure, and scalable in production.

Key responsibilities

• Design, implement, and maintain CI/CD pipelines for ML models and data workflows using AWS-native services and infrastructure-as-code.
• Operationalize models built on SageMaker, Bedrock, and Snowflake Cortex, including feature pipelines, training, batch/real-time inference, and monitoring.
• Build and manage data pipelines and feature stores using services such as AWS Glue, Lambda, Step Functions, and Snowflake.
• Implement observability for ML systems (logging, metrics, tracing, drift/quality monitoring) and establish SLOs/SLAs for production ML services.
• Automate environment provisioning, configuration, and dependency management across dev, test, and production.
• Partner with security and compliance teams to ensure ML workloads meet healthcare, privacy, and regulatory standards (e.g., HIPAA).
• Collaborate with ML engineers and data scientists to productionize notebooks and prototypes into robust, maintainable services.
• Contribute to best practices, standards, and documentation for ML platform and operations across the organization.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or a related field.
• 4+ years of experience in software engineering, data engineering, or ML engineering with at least 2+ years focused on MLOps or ML platform work.
• Strong proficiency with Python and experience integrating ML libraries or frameworks (e.g., scikit-learn, TensorFlow, PyTorch) into production workflows.
• Hands-on expertise with AWS services relevant to MLOps: SageMaker, Bedrock, IAM, CloudWatch, ECR, ECS/EKS or Lambda, S3, Step Functions, and Glue.
• Experience with Snowflake (including Snowflake Cortex), SQL, and building secure, performant data pipelines into and out of Snowflake.
• Proficiency with CI/CD tools (e.g., GitHub Actions, GitLab CI, CodePipeline) and infrastructure-as-code (e.g., Terraform, CloudFormation, CDK).
• Familiarity with containerization and orchestration (Docker, Kubernetes) and event streaming tools (e.g., Kafka) is a plus.
• Knowledge of software engineering best practices, including testing, code reviews, version control, and design for reliability and scalability.
• Experience in regulated domains or with healthcare data standards and regulations is a plus (e.g., HIPAA, FHIR, HL7).

Soft skills and benefits

• Excellent problem-solving and analytical skills with a focus on reliability and automation.
• Strong communication and collaboration abilities, including working cross-functionally with engineering, data science, and product teams.
• Ability to work independently in a fast-paced environment
• Competitive salary and benefits package.
• Opportunity to work on impactful ML platforms that improve healthcare outcomes.
• Collaborative, innovative environment with professional development and growth opportunities.

About the Role

Anaplan is looking for a skilled Python Machine Learning Developer to join our AI engineering organization. This is a crucial, hands-on developer role focused on building the robust backend systems that power our machine learning features. You are not just a developer; you are a software engineer who specializes in bringing ML models to life in a production environment. You will be responsible for designing, building, and deploying the APIs, data pipelines, and backend services necessary to integrate sophisticated machine learning capabilities into the Anaplan platform.

Key Responsibilities

• Design, build, and maintain scalable and reliable machine learning services and APIs using Python.
• Develop and productionize ML models, taking them from prototype to scalable, live systems.
• Construct and manage the data pipelines required for model training, validation, and inference.
• Build and interact with databases (both SQL and NoSQL) to store and retrieve data for ML applications.
• Write clean, high-quality, and well-tested code, adhering to software engineering best practices.
• Collaborate with data scientists, AI architects, and other engineers to integrate ML models into our products.
• Optimize applications for speed, scalability, and reliability.
• Contribute to our MLOps infrastructure to streamline the deployment and monitoring of machine learning models.

Required Qualifications

• Expert (6+ years) Python Programming: Strong, hands-on proficiency in Python for software development.
• Backend & API Development: Proven experience building and deploying backend services and RESTful APIs using frameworks like Flask, FastAPI, or Django.
• Database Proficiency: Solid experience with both SQL (e.g., PostgreSQL) and NoSQL (e.g., MongoDB, Redis) databases, including data modeling and query optimization.
• Machine Learning Libraries: Deep, practical knowledge of the core Python ML ecosystem:
• Data manipulation and analysis: Pandas, NumPy.
• Core ML frameworks: scikit-learn.
• Deep learning frameworks: Experience with TensorFlow or PyTorch.
• Strong understanding of software engineering principles, including data structures, algorithms, and design patterns.
• Experience with version control (Git) and CI/CD practices.
• Excellent problem-solving skills and the ability to write efficient, production-ready code.

Preferred Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
• Experience with cloud platforms (AWS, Azure, or GCP) and their ML services.
• Familiarity with containerization technologies like Docker and orchestration with Kubernetes.
• Experience with MLOps tools and principles (e.g., MLflow, Kubeflow).
• Knowledge of large-scale data processing frameworks like Spark or Dask.

What Makes This Role Exciting

This role places you at the critical intersection of software engineering and machine learning. You are a builder, responsible for creating the tangible systems that make our AI intelligent. You will tackle complex engineering challenges, from API design to database performance, all within the context of delivering cutting-edge machine learning features. At Anaplan, you will see your code run at scale, directly impacting a product used by leading global enterprises and solving real-world business problems.

About the Role

Anaplan is looking for a skilled Python Machine Learning Developer to join our AI engineering organization. This is a crucial, hands-on developer role focused on building the robust backend systems that power our machine learning features. You are not just a developer; you are a software engineer who specializes in bringing ML models to life in a production environment. You will be responsible for designing, building, and deploying the APIs, data pipelines, and backend services necessary to integrate sophisticated machine learning capabilities into the Anaplan platform.

Key Responsibilities

• Design, build, and maintain scalable and reliable machine learning services and APIs using Python.
• Develop and productionize ML models, taking them from prototype to scalable, live systems.
• Construct and manage the data pipelines required for model training, validation, and inference.
• Build and interact with databases (both SQL and NoSQL) to store and retrieve data for ML applications.
• Write clean, high-quality, and well-tested code, adhering to software engineering best practices.
• Collaborate with data scientists, AI architects, and other engineers to integrate ML models into our products.
• Optimize applications for speed, scalability, and reliability.
• Contribute to our MLOps infrastructure to streamline the deployment and monitoring of machine learning models.

Required Qualifications

• Expert (10+ years) Python Programming: Strong, hands-on proficiency in Python for software development.
• Backend & API Development: Proven experience building and deploying backend services and RESTful APIs using frameworks like Flask, FastAPI, or Django.
• Database Proficiency: Solid experience with both SQL (e.g., PostgreSQL) and NoSQL (e.g., MongoDB, Redis) databases, including data modeling and query optimization.
• Machine Learning Libraries: Deep, practical knowledge of the core Python ML ecosystem:
• Data manipulation and analysis: Pandas, NumPy.
• Core ML frameworks: scikit-learn.
• Deep learning frameworks: Experience with TensorFlow or PyTorch.
• Strong understanding of software engineering principles, including data structures, algorithms, and design patterns.
• Experience with version control (Git) and CI/CD practices.
• Excellent problem-solving skills and the ability to write efficient, production-ready code.

Preferred Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
• Experience with cloud platforms (AWS, Azure, or GCP) and their ML services.
• Familiarity with containerization technologies like Docker and orchestration with Kubernetes.
• Experience with MLOps tools and principles (e.g., MLflow, Kubeflow).
• Knowledge of large-scale data processing frameworks like Spark or Dask.

What Makes This Role Exciting

This role places you at the critical intersection of software engineering and machine learning. You are a builder, responsible for creating the tangible systems that make our AI intelligent. You will tackle complex engineering challenges, from API design to database performance, all within the context of delivering cutting-edge machine learning features. At Anaplan, you will see your code run at scale, directly impacting a product used by leading global enterprises and solving real-world business problems.

About the Role

We're seeking a versatile GenAI Software Engineer who can work across the full stack of GenAI applications, from model integration and prompt engineering to building intuitive user interfaces. You'll build production-ready AI features that empower business users to leverage the power of GenAI within their planning workflows, requiring both deep ML knowledge and strong software engineering skills.

Key Responsibilities

• Develop end-to-end GenAI features including backend API services, model integration, model monitoring, evaluations and deployments
• Integrate and optimize LLMs for specific use cases in business planning, including prompt engineering, RAG implementation
• Build conversational interfaces and agentic workflows that make complex planning tasks accessible through natural language
• Implement evaluation frameworks to measure and improve GenAI feature quality, including accuracy, latency, and user satisfaction metrics
• Design and develop APIs that expose AI capabilities to Anaplan's platform and third-party integrations
• Optimize model inference pipelines for performance, cost, and scalability in production environments
• Implement monitoring, logging, and observability for GenAI systems to track usage, errors, and model behaviour
• Collaborate with data scientists to productionize ML models and forecasting algorithms
• Write comprehensive tests including unit tests, integration tests, and prompt regression suites
• Participate in code reviews, technical design discussions, and knowledge-sharing sessions
• Stay current with GenAI research and tools, evaluating new models and techniques for potential adoption

Required Qualifications

• 3+ years of software engineering experience with 2+ years of understanding on ML/AI systems.
• Strong programming skills in Python including understanding of ML frameworks (PyTorch, TensorFlow, Transformers)
• Understanding or experience of building and deploying LLM-powered applications in production
• Understanding or experience of front-end development with React, TypeScript, and modern web technologies
• Understanding of RESTful API design, microservices architecture, and cloud infrastructure
• Experience with prompt engineering, RAG systems
• Understanding of ML fundamentals including NLP, time-series analysis, or recommender systems
• Familiarity with containerization (Docker), orchestration (Kubernetes), and CI/CD pipelines
• Excellent problem-solving skills and attention to detail
• Bachelor’s degree in computer science, Machine Learning, or related field

Preferred Qualifications

• Experience with GenAI frameworks (LangChain, LlamaIndex, Haystack, or similar)
• Knowledge of vector databases (Pinecone, Weaviate, Qdrant) and embedding models
• Experience with model serving frameworks (vLLM, TensorRT, Ray)
• Background in forecasting, planning, or analytics applications
• Familiarity with Anaplan or similar enterprise planning platforms
• Experience with A/B testing and experimentation frameworks for AI features
• Contributions to open-source ML projects or research publications
• Experience with model observability tools (LangSmith, W&B, MLflow)

What Makes This Role Exciting

• Lead a greenfield team building transformative AI capabilities from the ground up
• Work on cutting-edge conversational and agentic AI technologies
• Build user-facing AI features that directly impact how businesses plan and make decisions
• Experiment with the latest GenAI models and techniques
• Collaborate with talented engineers, data scientists, and product designers
• Solve unique challenges at the intersection of AI and enterprise software
• Grow your skills in both ML engineering and full-stack development

About the Role

Anaplan is looking for a skilled Python Machine Learning Developer to join our AI engineering organization. This is a crucial, hands-on developer role focused on building the robust backend systems that power our machine learning features. You are not just a developer; you are a software engineer who specializes in bringing ML models to life in a production environment. You will be responsible for designing, building, and deploying the APIs, data pipelines, and backend services necessary to integrate sophisticated machine learning capabilities into the Anaplan platform.

Key Responsibilities

• Design, build, and maintain scalable and reliable machine learning services and APIs using Python.
• Develop and productionize ML models, taking them from prototype to scalable, live systems.
• Construct and manage the data pipelines required for model training, validation, and inference.
• Build and interact with databases (both SQL and NoSQL) to store and retrieve data for ML applications.
• Write clean, high-quality, and well-tested code, adhering to software engineering best practices.
• Collaborate with data scientists, AI architects, and other engineers to integrate ML models into our products.
• Optimize applications for speed, scalability, and reliability.
• Contribute to our MLOps infrastructure to streamline the deployment and monitoring of machine learning models.

Required Qualifications

• Expert (6+ years) Python Programming: Strong, hands-on proficiency in Python for software development.
• Backend & API Development: Proven experience building and deploying backend services and RESTful APIs using frameworks like Flask, FastAPI, or Django.
• Database Proficiency: Solid experience with both SQL (e.g., PostgreSQL) and NoSQL (e.g., MongoDB, Redis) databases, including data modeling and query optimization.
• Machine Learning Libraries: Deep, practical knowledge of the core Python ML ecosystem:
• Data manipulation and analysis: Pandas, NumPy.
• Core ML frameworks: scikit-learn.
• Deep learning frameworks: Experience with TensorFlow or PyTorch.
• Strong understanding of software engineering principles, including data structures, algorithms, and design patterns.
• Experience with version control (Git) and CI/CD practices.
• Excellent problem-solving skills and the ability to write efficient, production-ready code.

Preferred Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
• Experience with cloud platforms (AWS, Azure, or GCP) and their ML services.
• Familiarity with containerization technologies like Docker and orchestration with Kubernetes.
• Experience with MLOps tools and principles (e.g., MLflow, Kubeflow).
• Knowledge of large-scale data processing frameworks like Spark or Dask.

What Makes This Role Exciting

This role places you at the critical intersection of software engineering and machine learning. You are a builder, responsible for creating the tangible systems that make our AI intelligent. You will tackle complex engineering challenges, from API design to database performance, all within the context of delivering cutting-edge machine learning features. At Anaplan, you will see your code run at scale, directly impacting a product used by leading global enterprises and solving real-world business problems.

Job Title: Senior Software Engineer, AI/ML or GenAI
Locations: Bangalore / Ahmedabad / Pune

Reports to: Director, Software Engineering

A quick snapshot…

As a Senior Software Engineer, you’ll be a key member in a team responsible for the development of scalable, reliable, and innovative AI/GenAI solutions. You’ll contribute to high-priority projects, ensuring maintainable code and producing high-quality, production-ready applications. You’ll operate with a high degree of technical expertise, strategic thinking, effective collaboration across diverse teams, while helping to mentor and elevate others to meet a very high technical bar.   

Why it’s a big deal…  

You will be a key contributor to delivering Conga’s AI roadmap, ensuring solutions meet high quality standards and timelines. You’ll be a core member of the team that will implement complex, large-scale AI systems. You’ll also have the opportunity to work cross-functionally to resolve issues, mentor junior members, and help to foster a culture of continuous learning and technical excellence. All of this adds up to an exciting, challenging, and always interesting place to work, where complex problems are found and solved every day.

Here's what we’re looking for…

Related Experience. You have 7+ years of professional software development experience, including 3+ years in AI/ML or GenAI. You have a proven track record of developing and deploying scalable, production-grade AI solutions. 

Technical expertise. You have:  

• Experience in Python and frameworks such as TensorFlow, PyTorch, FastAPI, LangChain, LangGraph, and KubeFlow.  

• Knowledge of AI/ML algorithms, generative models, and LLMs. 

• Proficiency with cloud platforms (e.g., GCP, AWS, Azure) and modern DevOps practices. 

• Strong understanding of distributed systems, microservices architecture, and database systems (SQL/NoSQL). 

Education. A bachelor’s degree in engineering or equivalent.

Here’s what will give you an edge…

Effective communication and interpersonal skills. You’re comfortable initiating and engaging in collaborative discussions. You are skilled at reading and adapting to different communication styles. When you speak, you are clear and concise. Your strong listening skills help to build trust and foster connections with our clients. They also ensure you collect the right information so you can resolve issues most expediently.

Initiative. You do not wait around for things to happen or for someone to tell you what to do. You are not only proactive about completing your own work, but when you sense the need to introduce a project that will benefit the team or the organization -- even if it’s outside your scope of work -- you put a proposal together, talk to the team about it, and own it. And that also goes back to having an entrepreneurial spirit.

Passionate Problem Solver. Proactive, self-driven, and enjoys solving complex problems, not just in the primary area of responsibility but across boundaries. Identify and implement best practices for coding as well as development processes and perform as a trusted contributor requiring little to no supervision and demonstrating the ability to meet deadlines, exceed goals, and create benchmarks for success.

#Li-VA1

Job Title: Staff Software Engineer, AI

Locations: Bangalore

Reports to: Sr. Manager, AI/ML.

A quick snapshot…

As a Staff Software Engineer, you will be a key contributor to the design, development, and deployment of advanced AI and generative AI-based products. You will drive technical innovation, lead complex projects, and collaborate closely with cross-functional teams to deliver high-quality, scalable, and maintainable solutions. This role requires a strong background in software development, AI/ML techniques, and DevOps practices, along with the ability to mentor junior engineers and contribute to strategic technical decisions.

Why it’s a big deal…

This is one of the critical roles in the project, where you will be an expert in product development, a good team player, and will lead and mentor your team members. We believe in using the best tools for the task at hand so the ability and desire to learn new programming languages and technologies is necessary. All of this adds up to an exciting, challenging, and always interesting place to work, where complex problems are found and solved every day. This role determines the root cause for the most complex software issues and develops practical, efficient, and permanent technical solutions.

Are you the person we’re looking for?

Experience: 8+ years of professional software development experience, including significant experience with AI/ML or GenAI applications. Demonstrated expertise in building scalable, production-grade software solutions.

Advanced Software Development: Design, develop, and optimize high-quality code for complex software applications and systems, maintaining high standards of performance, scalability, and maintainability. Drive best practices in code quality, documentation, and test coverage.

GenAI Product Development: Lead end-to-end development of generative AI solutions, from data collection and model training to deployment and optimization. Experiment with cutting-edge generative AI techniques to enhance product capabilities and performance.

Technical Leadership: Take ownership of architecture and technical decisions for AI/ML projects. Mentor junior engineers, review code for adherence to best practices, and ensure the team follows a high standard of technical excellence.

Project Ownership: Lead execution and delivery of features, managing project scope, timelines, and priorities in collaboration with product managers. Proactively identify and mitigate risks to ensure successful, on-time project completion.

Architectural Design: Contribute to the architectural design and planning of new features, ensuring solutions are scalable, reliable, and maintainable. Engage in technical reviews with peers and stakeholders, promoting a product suite mindset.

Code Review & Best Practices: Conduct rigorous code reviews to ensure adherence to industry best practices in coding standards, maintainability, and performance optimization. Provide feedback that supports team growth and technical improvement.

Testing & Quality Assurance: Design and implement robust test suites to ensure code quality and system reliability. Advocate for test automation and the use of CI/CD pipelines to streamline testing processes and maintain service health.

Service Health & Reliability: Monitor and maintain the health of deployed services, utilizing telemetry and performance indicators to proactively address potential issues. Perform root cause analysis for incidents and drive preventive measures for improved system reliability.

Educational : Bachelor’s degree in computer science, Engineering, or a related technical field; Master’s degree preferred.

Here’s what will give you an edge…

Technical Expertise: Advanced proficiency in Python, FastAPI, PyTest, Celery, and other Python frameworks. Deep knowledge of software design patterns, object-oriented programming, and concurrency.

Cloud & DevOps Proficiency: Extensive experience with cloud technologies (e.g., GCP, AWS, Azure), containerization (e.g., Docker, Kubernetes), and CI/CD practices. Strong understanding of version control systems (e.g., GitHub) and work tracking tools (e.g., JIRA).

AI/GenAI Knowledge: Familiarity with GenAI frameworks (e.g., LangChain, LangGraph), MLOps, and AI lifecycle management. Experience with model deployment and monitoring in cloud environments.

Preferred Skill sets/Tools:

AI & Machine Learning: Hands-on experience with advanced ML algorithms, including generative models, NLP, and transformers. Knowledge of industry-standard AI frameworks (e.g., TensorFlow, PyTorch) and experience with data preprocessing and model evaluation.

Data & Analytics Tools: Proficiency with relational and NoSQL databases (e.g., MongoDB, MSSQL, PostgreSQL) and analytics platforms (e.g., BigQuery, Snowflake, Tableau). Experience with messaging systems (e.g., Kafka) is a plus.

Testing & Quality: Experience with test automation tools (e.g., PyTest, xUnit) and CI/CD tooling such as Terraform and GitHub Actions. Strong emphasis on building resilient and testable software.

Advanced Cloud Knowledge: Proficiency with GCP technologies such as VertexAI, BigQuery, GKE, GCS, and DataFlow, with a focus on deploying AI models at scale.

#LI-UB1

Job Title: Senior Software Engineer
Locations: Bangalore
Reports to: Director, Software Engineering

A quick snapshot…
As a Senior Software Engineer, you’ll be a key member in a team responsible for the development of scalable, reliable, and innovative AI/GenAI solutions. You’ll contribute to high-priority projects, ensuring maintainable code and producing high-quality, production-ready applications. You’ll operate with a high degree of technical expertise, strategic thinking, effective collaboration across diverse teams, while helping to mentor and elevate others to meet a very high technical bar.   

Why it’s a big deal…  

You will be a key contributor to delivering Conga’s AI roadmap, ensuring solutions meet high quality standards and timelines. You’ll be a core member of the team that will implement complex, large-scale AI systems. You’ll also have the opportunity to work cross-functionally to resolve issues, mentor junior members, and help to foster a culture of continuous learning and technical excellence. All of this adds up to an exciting, challenging, and always interesting place to work, where complex problems are found and solved every day.

Here's what we’re looking for…

Related Experience. You have 7+ years of professional software development experience, including 3+ years in AI/ML or GenAI. You have a proven track record of developing and deploying scalable, production-grade AI solutions. 

Technical expertise. You have:  

• Experience in Python and frameworks such as TensorFlow, PyTorch, FastAPI, LangChain, LangGraph, and KubeFlow.  

• Knowledge of AI/ML algorithms, generative models, and LLMs. 

• Proficiency with cloud platforms (e.g., GCP, AWS, Azure) and modern DevOps practices. 

• Strong understanding of distributed systems, microservices architecture, and database systems (SQL/NoSQL). 

Education. A bachelor’s degree in engineering or equivalent.

Here’s what will give you an edge…

Effective communication and interpersonal skills. You’re comfortable initiating and engaging in collaborative discussions. You are skilled at reading and adapting to different communication styles. When you speak, you are clear and concise. Your strong listening skills help to build trust and foster connections with our clients. They also ensure you collect the right information so you can resolve issues most expediently.

Initiative. You do not wait around for things to happen or for someone to tell you what to do. You are not only proactive about completing your own work, but when you sense the need to introduce a project that will benefit the team or the organization -- even if it’s outside your scope of work -- you put a proposal together, talk to the team about it, and own it. And that also goes back to having an entrepreneurial spirit.

Passionate Problem Solver. Proactive, self-driven, and enjoys solving complex problems, not just in the primary area of responsibility but across boundaries. Identify and implement best practices for coding as well as development processes and perform as a trusted contributor requiring little to no supervision and demonstrating the ability to meet deadlines, exceed goals, and create benchmarks for success.

#Li-VA1

Bloomreach is seeking a seasoned Staff Machine Learning Engineer to own the design and implementation of cutting-edge AI and GenAI driven algorithmic components for search, recommendation and behavioral insights that are used to personalize digital experiences for our customers. Our centralized data science team spanned across multiple geographies, is responsible for the data science modules that power all the products of the company, including Search Relevance, Recommendation, User Personalization, User Segmentations, Content Intelligence and Conversational Commerce. We invent and apply machine learning, data mining, and information retrieval algorithms to understand, identify, and improve web content discovery. We have built industry leading algorithms in search and recommendations for the commerce space that serve the most relevant experiences using Artificial Intelligence with the goal-building AI driven experiences beyond commerce.

Your Responsibilities:

• Design, develop, and enhance ML/AI models which mainly power Search and Recommendation.
• Process historical data, search queries, product catalog, and images to extract hidden relations and features.
• Conduct research to explore ongoing cutting-edge ML techniques (especially deep learning) and conduct a quick POC.
• Work closely with Data Engineers and Senior Data Scientists to integrate and scale ML components to a production-level that can handle terabytes of data.
• Continuously learn and stay up to date with the current state-of-the-art techniques by reading research papers and attending AI/ML conferences.
• Own deep data analysis and A/B test debugging, proactively identifying root causes, assessing impact, and providing clear, data-driven direction on next steps (e.g., what to fix and how to adjust experiment design).

Qualifications:

• BS/MS degree in Computer Science or a related discipline with a strong mathematical foundation and excellent programming skills (primarily Python)
• 8+ years experience building ML-driven fast and scalable ML/analytical algorithms in a corporate/startup environment.
• Strong awareness and understanding of recent trends in Generative AI and LLMs. Experience in working with GenAI stack will be treated as strong credentials.
• Strong understanding of various machine learning and natural language processing technologies, such as classification, information retrieval, clustering, knowledge graph, semi-supervised learning and ranking.
• Excellent exploratory data analysis skills with the ability to slice and dice data at scale using SQL in Redshift/BigQuery.
• Good problem solving and analytical skills. Ability to learn and adapt to newer ML technologies.
• Exposure to deep learning stack (PyTorch/Keras/TensorFlow) and techniques (Representation/Transfer Learning, RNN/LSTM, Transformers).
• Experience working with Big Data in a cloud based production environment (AWS/GCP/Azure).
• Effective communication skill in English, both verbally and in written form.

About Frontier

Frontier is a subsidiary of Fresh Prints. Fresh Prints is a New York based, fast-growing, fully-remote, 150-person company that has most of our team in India and Philippines. A few years ago Fresh Prints started helping other fast-growing companies build their teams. We got so good at it that we decided to spin out a new company to focus exclusively on that and call it Frontier.

Here at Frontier, we help companies grow full-time, cross-functional teams abroad. We hire the smartest people, and we place them into the best companies. If you like one of the Frontier roles, and you apply, and you’re accepted, we’ll screen you with a couple of internal interviews, and will work on getting you an interview for a full-time job within the month. Think of us as your personal talent agent, and good luck with the application :)

About the client

Balto’s mission is to power a new era of knowledge work in the contact center, and we're creating awesome technology to do just that. If you're excited by the opportunity to join a dynamic team initiating a technological revolution in Real-Time Guidance, Balto is for you.

More than just a company, Balto is a community. A community committed to empowering each of our members. This mission is at the heart of our organization. As a member of our Technical Success team, you’ll act as the voice of the user, drive efficient implementation & product engagement from onboarding to continued adoption, and investigate solutions for complex technical issues. 

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

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.

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.

About the role

Crunchyroll is growing and changing, presenting unique challenges and opportunities to support millions of anime fans around the world. The AI/ML team provides seamless help to our internal stakeholders, ensuring an exceptional experience for all Crunchyroll fans.

• Lead and mentor a team of data scientists focused on developing and deploying ML solutions including GNNs, LLM-based applications, and fraud detection models.
• Define and drive the roadmap for AI/ML initiatives across Crunchyroll’s product and platform ecosystem.
• Guide the development of robust ML pipelines and infrastructure, working closely with data engineering, software engineering, and DevOps teams.
• Establish best practices for experimentation, model evaluation, A/B testing, and continuous learning in production environments.
• Work with stakeholders across business, marketing, security, and content teams to identify AI opportunities and translate them into actionable projects.
• Ensure responsible AI/ML development by emphasizing model interpretability, performance, and fairness.
• Own operational metrics around model impact, latency, cost, and system scalability.
• Foster a strong team culture centered on innovation, curiosity, collaboration, and continuous learning.

About You

We get excited about candidates, like you, because...

• Bachelor's or Master's in Computer Science, Statistics, Data Science, or a related quantitative field.
• 8+ years of industry experience in data science or applied ML, with 4+ years of people leadership experience.
• Proven track record of delivering production ML systems that solve real-world business problems.
• Deep knowledge of ML/AI frameworks (e.g., PyTorch, TensorFlow, HuggingFace) and experience with applied NLP, GNNs, GraphRAG, and embeddings.
• Experience building systems leveraging Graph Databases, Vector Stores (e.g., FAISS, Pinecone), and cloud-native ML stacks (SageMaker, Databricks, etc.).
• Strong technical leadership, with the ability to direct teams to develop optimal ML solutions and guide research-to-production lifecycle.
• Excellent communication and stakeholder management skills; able to translate between business and technical worlds.
• A passion for building high-performing teams, mentoring others, and fostering a learning-first environment.

About the Team

The R&D team is dedicated to developing, testing, and validating robust and scalable machine learning models that drive business objectives. Our focus includes enhancing operational processes through AI/ML solutions, such as trend analysis, anomaly detection, and the deployment of large language models (LLMs) for tasks like querying system health. Another major focus area is preserving, and improving customer experience and retention. We closely work with our stakeholders to ensure AI/ML objectives are clearly defined.

About the role

We are seeking a Senior Machine Learning Engineer in the Hyderabad area to design, build, and scale machine learning systems that power personalized and data-driven experiences across our digital entertainment ecosystem — including paid VOD streaming, Manga reading, Merchandising, Mobile Gaming, and Music Video platforms. The role will be reporting to the Manager of Machine Learning.

You will work at the intersection of user behavior, content intelligence, and product engagement, building models and systems that both enhance user experience (e.g., personalization, discovery, lifecycle optimization) and generate actionable business insights and services for internal stakeholders. As a senior individual contributor, you will own high-impact initiatives end-to-end and play a key role in shaping the technical direction of ML systems across products.

Core Areas of Responsibility

• Design, develop, and deploy scalable machine learning models that enhance personalization, discovery, engagement, and monetization across multiple product verticals.
• Lead end-to-end ML projects from problem framing and data exploration to production deployment and monitoring.
• Build and optimize robust data pipelines and feature engineering workflows for large-scale behavioral and content data.
• Design and execute rigorous experimentation frameworks (e.g., A/B testing, offline evaluation) to measure model impact.
• Collaborate closely with Product, Engineering, Analytics, and business stakeholders to translate product goals into ML solutions.
• Improve system reliability, scalability, and performance of production ML services.
• Mentor junior engineers and contribute to raising the team’s technical standards and best practices.
• Contribute to the evolution of ML architecture, tooling, and MLOps practices across the organization.

About You

Required Qualifications

• 8+ years of experience building and deploying machine learning systems in production environments
• Strong foundation in machine learning algorithms, statistics, and model evaluation techniques
• Experience working with large-scale user behavior or content datasets
• Proficiency in Python and common ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn, xgboost)
• Experience with distributed data processing and data pipeline technologies
• Strong understanding of experimentation methodologies and performance measurement
• Ability to operate independently and drive ambiguous problems to impactful solutions

Preferred Qualifications

• Experience with recommendation systems, ranking models, personalization, or user lifecycle modeling
• Experience in subscription-based digital products, streaming media, gaming, or e-commerce platforms
• Familiarity with cloud infrastructure and production ML services
• Experience optimizing models for real-time or near real-time user-facing applications
  
  

What Success Looks Like

• ML systems you build measurably improve user engagement, retention, or monetization
• Models are reliable, scalable, and well-integrated into product workflows
• Stakeholders trust your technical judgment and rely on your work to inform product direction
• You elevate the team’s engineering rigor and contribute meaningfully to long-term ML platform evolution

About the Team

You will join a fast growing team of Data Scientists, Machine Learning Engineers, and AI Engineers, united by a passion for leveraging data and AI to create transformative solutions. Our team delivers both consumer-facing product features that enhance the streaming experience for millions of users and stakeholder-oriented solutions that empower internal teams with actionable insights. From building personalized recommendation systems to developing innovative tools like our stakeholder-facing chatbot, we combine cutting-edge machine learning, robust data pipelines, and advanced AI to drive impact across the organization. Collaboration, creativity, and a commitment to excellence define our team’s culture as we work together to push the boundaries of what’s possible in streaming and data-driven decision-making.

At Reltio®, we believe data should fuel business success. Reltio’s AI-powered data unification and management capabilities—encompassing entity resolution, multi-domain master data management (MDM), and data products—transform siloed data from disparate sources into unified, trusted, and interoperable data. Reltio Data Cloud™ delivers interoperable data where and when it's needed, empowering data and analytics leaders with unparalleled business responsiveness. Leading enterprise brands—across multiple industries around the globe—rely on our award-winning data unification and cloud-native MDM capabilities to improve efficiency, manage risk and drive growth.

At Reltio, our values guide everything we do. With an unyielding commitment to prioritizing our “Customer First”, we strive to ensure their success. We embrace our differences and are “Better Together” as One Reltio. We are always looking to “Simplify and Share” our knowledge when we collaborate to remove obstacles for each other. We hold ourselves accountable for our actions and outcomes and strive for excellence. We “Own It”. Every day, we innovate and evolve, so that today is “Always Better Than Yesterday”. If you share and embody these values, we invite you to join our team at Reltio and contribute to our mission of excellence.

Reltio has earned numerous awards and top rankings for our technology, our culture and our people. Reltio was founded on a distributed workforce and offers flexible work arrangements to help our people manage their personal and professional lives. If you’re ready to work on unrivaled technology where your desire to be part of a collaborative team is met with a laser-focused mission to enable digital transformation with connected data, let’s talk!

About the Role

We are seeking a Senior Backend Engineer with a strong foundation in Java, solid Python capabilities, and hands-on experience building Agentic AI applications that integrate with Large Language Models (LLMs). This role blends traditional backend engineering expertise with next-generation AI agentic systems development, requiring not just system design skills, but also creativity in prompt engineering, AI product development and working with data-rich environments.

You will contribute to the design and implementation of intelligent backend services that coordinate LLMs, agents, and data workflows to support enterprise-grade agentic systems.

Key Responsibilities

• Develop robust, scalable Java/Python based backend systems that enable the orchestration of Agentic AI workflows.
• Develop state-of-the-art AI/ML models for solving real-world data management challenges such as entity resolution, classification, similarity matching, and anomaly detection.
• Integrate LLMs (e.g., OpenAI, Mistral, Claude, LLaMA) into backend pipelines to power autonomous or semi-autonomous decision-making.
• Develop scalable ML workflows using Spark, MLlib, PyTorch, TensorFlow, or MLFlow, with seamless integration into production systems.
• Translate business needs into technical design and collaborate with data scientists, product managers, and platform engineers to operationalize models.
• Work closely with various stakeholders to design agent architectures and LLM toolchains (using frameworks like LangGraph, Crew AI, AutoGen, etc.).
• Implement services and APIs that manage prompt chaining, tool invocation, and contextual memory for agents.
• Collaborate with data engineers to ensure clean, efficient, and real-time access to structured and semi-structured data.
• Apply prompt engineering best practices to improve agent behavior, task accuracy, and adaptability.
• Monitor and optimize service performance, reliability, and scalability in production environments.
• Continuously monitor and improve model performance using feedback loops, A/B testing, drift detection, and retraining strategies.
• Contribute to code reviews, mentoring, and best practices for hybrid backend/AI development.

Required Qualifications

• 5+ years of overall experience in backend engineering, with strong proficiency in Java for scalable, distributed systems.
• 2+ years of experience in developing and deploying machine learning models and AI products in production environments.
• Experience in Agentic AI systems development using tools such as LangGraph, Crew AI, AutoGen, or similar.
• Proficiency in Python (NumPy, scikit-learn, pandas, PyTorch/TensorFlow) and experience with large-scale data processing tools (Spark, Kafka, Airflow).
• Experience integrating or orchestrating LLMs within business workflows or intelligent assistants.
• Solid understanding of prompt engineering techniques (e.g., system messages, chaining, tool invocation prompts).
• Familiarity with data engineering concepts, including pipelines, data models, and ETL workflows.
• Strong grasp of object-oriented design, data structures, and algorithms.

Preferred Qualifications

• Experience with LLM orchestration frameworks (e.g., LangChain, LlamaIndex, RAG pipelines).
• Background in building microservices or backend systems for data-rich AI/ML platforms.
• Experience with vector databases, embedding services, or semantic search integration.
• Knowledge of cloud platforms (AWS, GCP, or Azure), containerization (Docker), and DevOps best practices.
• Experience in developing LLM-powered agents, copilots, or task bots.

What We Offer

• Opportunity to work on cutting-edge backend and AI systems, including agentic automation and LLM innovation.
• A flexible hybrid work model in our Bangalore office.
• Competitive compensation with performance-based rewards.
• A culture that promotes engineering excellence, experimentation, and growth.Access to learning platforms, technical workshops, and industry-leading AI research.

Why Join Reltio?*

• Health & Wellness:
  • Comprehensive Group medical insurance including your parents with additional top-up options.
  • Accidental Insurance
  • Life insurance
  • Free online unlimited doctor consultations
  • An Employee Assistance Program (EAP)
• Work-Life Balance:
  • 36 annual leaves, which includes Sick leaves – 18, Earned Leaves - 18
  • 26 weeks of maternity leave, 15 days of paternity leave
  • Very unique to Reltio - 01 week of additional off as recharge week every year globally
• Support for home office setup:
  • Home office setup allowance.
• Stay Connected, Work Flexibly: Mobile & Internet Reimbursement
• No need to pack a lunch—we’ve got you covered with a free meal.And many more…..

What You’ll Do:

• Architect the Future of AI Infrastructure: You will design, build, and own the end-to-end platform that supports the entire lifecycle of our ML models—from massive-scale distributed training to ultra-low-latency, highly-available inference.
• Optimize and Serve Cutting-Edge Models: You'll implement and scale sophisticated inference stacks for LLMs using frameworks like vLLM, TensorRT-LLM, or SGLang. You’ll solve complex challenges in throughput, latency, token streaming, and automated scaling to deliver a seamless user experience. 
• Empower AI Innovation: You will act as a strategic partner to our AI Research and Data Science teams. You’ll create a seamless developer experience that accelerates their ability to experiment, fine-tune, and deploy groundbreaking models with velocity and confidence.
• Automate Everything: You'll develop robust CI/CD/CT (Continuous Training) pipelines using tools like Argo Workflows, ArgoCD, and GitHub Actions to automate model validation, deployment, and lifecycle management, ensuring our systems are both agile and rock-solid.

What are we looking for

• Experience: 5+ years in infrastructure or software engineering, with at least 2+ years laser-focused on MLOps or ML infrastructure for large-scale distributed systems.
• Education: A Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
• Kubernetes & Cloud Native Expertise: Deep, hands-on expertise with Kubernetes in production. You are fluent in the cloud-native ecosystem, including Helm, ArgoCD, and Argo Workflows.
• GPU & Cloud Mastery: Optimize the platform’s performance and scalability, considering factors such as GPU resource utilization, data ingestion, model training, and deployment.
• Modern LLM Serving Experience: Hands-on experience with modern LLM inference serving frameworks (e.g., vLLM, SGLang, Triton Inference Server, Ray Serve). You understand the unique challenges of serving generative models.
• Strong Coder: Strong programming proficiency in Python or Go, with experience using ML frameworks like PyTorch, Jax, TensorFlow.
• Observability Mindset: A passion for building observable and resilient systems using modern monitoring tools (e.g., Prometheus, Grafana, OpenTelemetry).

We would love to see:

• Deep performance optimization skills, including writing custom inference kernels in CUDA or Triton to accelerate model performance beyond what off-the-shelf frameworks provide.
• Experience with model optimization techniques like quantization, distillation, and speculative decoding.
• Exposure to training and serving multi-modal models (e.g., text-to-image, vision-language).
• Knowledge of AI safety and evaluation frameworks for monitoring model performance for things like bias, toxicity, and hallucinations.

As part of our hiring process, shortlisted candidates will undergo a Background Verification (BGV). By applying, you consent to sharing personal information required for this process. Any offer made will be subject to successful completion of the BGV.

Senior Data Engineer/Data Ops (m/f/d)

Remote EMEA/ Remote India
________________________

Hello 👋 I am Adriano, Machine Learning Lead at Kayzen, and I am now looking for a Senior Data Engineer who will be a part of the machine learning engineering team bridging the gap between data science and ad systems engineering team 🙌

But wait, you have not heard of Kayzen before? 😃 

Kayzen is a mobile demand-side platform (DSP) dedicated to democratizing programmatic advertising. We enable leading apps, agencies, media buyers, and brands to run programmatic customer acquisition, retargeting, and brand performance campaigns through our self-serve and managed service options. Built on the three core pillars of performance, transparency, and control, Kayzen powers the world’s best mobile marketing teams with bespoke solutions that fuel business growth and deliver a competitive advantage. With an unprecedented scale of 300B+ daily ad requests from 1.6B+ unique users worldwide, we serve up to 1B+ ads per day in 180 countries. Kayzen is accessible through our APIs and user interface.

The role

Are you excited about data? Will you take on the challenge to help us make Kayzen a ML first organization leading the AdTech space? Do you want to change the way we as an organization manage our data and do business? Are you interested in how billions of data points flow through various systems & data pipelines and how it is governed to generate knowledge and value? If your answer is “yes” to all these questions, if you are a problem solver and a team player, we would love to meet you!

Day to day

As a Data Engineer/Data Ops, you will work to create innovative solutions for handling peta-bytes of data with billions of rows & joins. Your work can vary from creating real time and offline features generation pipelines to managing our data infrastructure to be reliable and fast!
You’ll be responsible for:

• Program and maintain our data pipelines that fuels our on-premise/cloud data warehouse used to generate and serve our models
• Maintain and improve our fleet of data servers (the software), making sure they are reliable and able to process our billions of logs and data points
• Develop and productionize data pipelines for our ML models in both bare-metal and the cloud environment.
• Make suggestions and lead projects to improve our data processing capabilities
• Contribute to the team enabling us to be always better

Sounds like you? 😉

We are looking for a candidate with a minimum 5+ yrs of professional experience in creating and maintaining big data pipelines, identifying data related process improvements, maintaining Kubernetes, Hadoop and Spark infrastructure. 

• Bachelor's/Master’s degree in a quantitative field of Mathematics, Physics, Computer Science, Machine learning Engineering, Business Analytics, Information Management or related field.
• You know relevant programming languages (Python, Java, etc)
• Expert in SQL & NoSQL and big data processing pipelines (we use Python, Spark, Airflow)
• Have proven experience managing data infrastructure that can store and process Petabytes of data (we use Hadoop, Spark)
• Kubernetes wizard. LLM symbiotic. 
• You have proven affinity with data
• You have strong analytical and problem-solving skills
• You can translate business requirements into data solutions
• You have excellent stakeholder management skills.
• Previous experience with Clickhouse is a plus
• Previous experience with ad-tech is a plus
• Experience with Real time big data processing is a plus
• General understanding of Machine Learning techniques (Neural Networks, Random Forest, etc.) and ML frameworks (Mlflow, PyTorch, Tensorflow, etc.) is a plus

What do we offer?

• Exceptional career growth and learning opportunity
• A unique opportunity to be part of an experienced team of industry experts and entrepreneurs who bring massive change to the Adtech market
• Direct, day-to-day work experience with the management
• A fun, driven, and multinational team located across Germany, India, Argentina, Ukraine, Turkey, the UK and soon more countries
• A flexible work-from-home arrangement
• A 500-dollar home-office setup budget
• A 1000-dollar annual learning and development budget

WHO YOU ARE

You are a passionate Python and AI/ML Engineer minimum 4 years of hands-on experience building intelligent systems. You thrive in fast-paced environments, love solving complex problems with data and algorithms, and take pride in delivering AI solutions that create real business impact. You have experience with cutting-edge Generative AI, scalable ML pipelines, and production-grade systems and you're energized by working at the frontier of what AI can do.

WHAT YOU'LL DO

1. Design, develop, and deploy machine learning models and Generative AI solutions — including classification, clustering, summarization, search & ranking, and information extraction.
2. Own end-to-end ML pipelines — from data ingestion and preprocessing through model training, deployment, and production monitoring.
3. Collaborate with cross-functional teams to translate business requirements into AI-driven features — applying NLP, outlier detection, and deep learning techniques where applicable.
4. Build robust, scalable, and well-documented Python-based RESTful APIs to expose ML models and AI services in production environments.
5. Optimize database interactions and ensure efficient data storage and retrieval for AI applications across SQL and NoSQL systems.
6. Stay current with the latest advances in AI/ML — integrating emerging approaches such as RAG pipelines, LLM fine-tuning, and vector search into live products.

WHAT YOU'LL NEED 

Python
Strong hands-on proficiency for building, scripting, and deploying AI/ML systems.
NumPy · Pandas · FastAPI · Scikit-learn
Machine Learning
Applied expertise across supervised, unsupervised, and deep learning — classification, clustering, outlier detection.
PyTorch · TensorFlow · XGBoost · DBSCAN

Generative AI (2+ yrs)
Hands-on experience building with LLMs — prompt engineering, RAG pipelines, summarization, and AI-powered features.
LLMs · RAG · Prompt Eng. · Fine-tuning

NLP & Search / Ranking
Processes language and builds relevance engines — NER, embeddings, semantic search, and ranking models.
spaCy · BERT · FAISS · Elasticsearch

API Development
Designs and ships secure, well-documented RESTful APIs exposing ML models as production-ready services.
REST · FastAPI · OAuth2 · Swagger

Databases
Proficient in SQL and NoSQL stores for structured and unstructured data pipelines supporting AI workloads.
PostgreSQL · MongoDB · Vector DBs

GOOD TO HAVE

Cloud Platforms
Deploys and scales AI workloads on AWS, Azure, or GCP.
AWS · Azure

TypeScript / JavaScript
Frontend or full-stack exposure for building ML-powered product interfaces.
TypeScript · React · Node.js

MLOps
Manages the ML lifecycle — tracking, versioning, and pipeline automation.
MLflow · Kubeflow · CI/CD

Containerization & Orchestration
Packages and scales AI services using containers and cluster management.
Docker · Kubernetes

About HG Insights

Headquartered in Santa Barbara, California, HG Insights is the global leader in technology intelligence. We help the world’s most innovative companies accelerate their go-to-market efforts with precision through advanced data science methodologies and proprietary data assets. We offer a culture that blends innovation, collaboration, and growth, where each team member is empowered to make a measurable impact.

Role Overview

We are looking for a Staff/Senior Machine Learning Engineer to join our growing AI and Data Platform team in Pune, India. In this role, you will be responsible for designing, building, and scaling ML systems that power our core data intelligence products. You’ll work at the intersection of data engineering and machine learning, collaborating closely with data scientists, software engineers, and product teams to turn models and agents into robust, production-ready systems.

This is a high-impact role suited for someone who thrives on ownership, scalability, and deploying real-world ML and AI solutions at scale.

Key Responsibilities

ML & AI System Development

• Design and build end-to-end ML pipelines, from data ingestion and feature engineering to model training, serving, and monitoring.
• Productionize AI agents, including LLM-backed workflows, multi-step tool use, and API orchestration.
• Collaborate with data scientists to bring experimental models into stable, high-performing production systems.
  
  

MLOps & Infrastructure

• Implement and maintain MLOps workflows (CI/CD for ML), tracking experiments, managing model versions, and automating retraining.
• Set up observability for models and agents, including tracing, logging, latency/error tracking, and fallback logic.
• Ensure infrastructure supports scalability, performance, and compliance requirements.
  
  

Technical Leadership & Collaboration

• Lead technical architecture for key AI and ML systems, ensuring maintainability and extensibility.
• Partner with product and platform teams to translate business needs into reliable and performant ML solutions.
• Mentor junior engineers and help elevate technical practices across the engineering org.

Minimum Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
• 8+ years of industry experience, with at least 4+ years in ML engineering or MLOps.
• Strong programming skills in Python and experience with ML libraries such as PyTorch, TensorFlow, and scikit-learn.
• Experience deploying AI agents in production, including retrieval-augmented generation (RAG), multi-step reasoning, and tool-use orchestration.
• Familiarity with LangChain, LlamaIndex, Haystack, or similar frameworks for agent development.
• Hands-on with LLMs (OpenAI, Anthropic, Cohere, etc.), embedding models, and vector store integration.
• Expertise in MLOps tools like MLflow, Airflow, SageMaker, or Kubeflow.
• Experience with cloud platforms (preferably AWS), Docker/Kubernetes, and large-scale data systems (e.g., Snowflake, Databricks).
• Excellent problem-solving and system design skills, including CI/CD, testing, and infrastructure-as-code.
  
  

Preferred Qualifications

• Experience with streaming pipelines, online inference, and model monitoring at scale.
• Exposure to agent memory, feedback loops, or AI workflow orchestration in customer-facing products.
• Prior contributions to open-source ML or LLM projects are a plus.
  
  

Why Join HG Insights?

• Work on high-impact AI products used by global enterprise customers.
• Lead the ML engineering strategy and shape our AI platform.
• Competitive compensation and benefits tailored for India-based employees.
• A collaborative and innovation-focused team environment.
  
  

Ready to build the future of AI infrastructure? Apply now to join HG Insights as a Staff Machine Learning Engineer in Pune.

EnCharge AI is a leader in advanced AI hardware and software systems for edge-to-cloud computing. EnCharge’s robust and scalable next-generation in-memory computing technology provides orders-of-magnitude higher compute efficiency and density compared to today’s best-in-class solutions. The high-performance architecture is coupled with seamless software integration and will enable the immense potential of AI to be accessible in power, energy, and space constrained applications. EnCharge AI launched in 2022 and is led by veteran technologists with backgrounds in semiconductor design and AI systems.

About the Role

EnCharge AI is seeking a highly skilled and experienced AI Compiler Engineer to spearhead the efforts in developing and optimizing graph compilers tailored to cutting-edge AI and ML workloads. You will collaborate with hardware architects, and AI researchers to enhance performance, optimize computation graphs, and enable efficient model deployment on EnCharge’s Inference Accelerators. 

Responsibilities

• Architect, design, and implement optimizations for AI model execution on graph compilers to improve performance, reduce latency, and maximize hardware utilization.
• Work closely with ML researchers, hardware engineers, and software developers to design and deploy AI models, understanding and addressing hardware-specific challenges.
• Work on performance optimizations for neural network models, such as layer fusion, operator fusion, and graph-level transformations.
• Develop compiler optimizations and passes that convert high-level AI models (e.g., from TensorFlow, PyTorch) into intermediate representations (IR).
• Implement parsing, semantic analysis, and IR generation for deep learning frameworks.
• Research and integrate the latest advancements in compiler design, ML model optimizations, and hardware acceleration into graph compilers.
• Provide leadership, mentorship, and technical guidance to a team of engineers focused on graph compiler optimizations. 

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or related field (Ph.D. preferred).
• 3+ years in compiler development, with a strong focus on AI or ML graph compilers.
• Proficiency in AI graph compiler frameworks (e.g., MLIR, Torch-FX)
• Solid background in hardware architectures (e.g., GPUs, TPUs, ASICs) and optimization techniques such as fusion, quantization, and tiling.
• Familiarity with neural networks operators and code generation.
• Strong understanding of intermediate representations, code parsing, and semantic analysis in compiler design.
• Proficiency in C++, Python, or other programming languages commonly used in compiler development.
• Open-source contributions to AI software frameworks and libraries is a plus
• Demonstrated experience leading and mentoring engineering teams with successful project delivery. 

EnchargeAI is an equal employment opportunity employer in the United States.

Role: GenAI Lead Engineer

Experience: 8+ years total (with significant hands-on GenAI / LLM work)

Job Overview:

We are seeking an innovative and highly skilled Lead Generative AI (GenAI) Engineer to spearhead the design, development, and deployment of advanced AI-powered solutions. In this role, you will lead a team of engineers and data scientists to harness cutting-edge Generative AI technologies and implement them to solve complex business problems, enhance user experiences, and drive innovation. This role combines deep technical expertise, leadership, and a strong understanding of AI trends and tools.

Key Responsibilities:

• Technical Leadership:
• Lead the end-to-end design and implementation of Generative AI solutions.
• Provide technical guidance and mentorship to engineers and data scientists working on GenAI projects.
• Stay updated with the latest trends, research, and advancements in Generative AI and Large Language Models (LLMs).
• Solution Development:
• Architect, train, and fine-tune state-of-the-art LLMs and generative AI models
• Develop and optimize pipelines for prompt engineering, retrieval-augmented generation (RAG), and domain-specific fine-tuning.
• Develop and deploy generative AI models, particularly focusing on ChatGPT, using Python on Azure or AWS Platform or .Net on Azure platform
• Ensure scalability, performance, and security of AI solutions deployed in production.
• Integration and Deployment:
• API Development: Ability to define and deliver API access for GenAI services, facilitating integration with other systems and applications.
• Collaborate with software engineering teams to integrate GenAI solutions into enterprise applications and services.
• Utilize cloud platforms (e.g., Azure, AWS, or GCP) to deploy and manage AI models and APIs.
• Leverage MLOps practices for continuous model monitoring, retraining, and improvement.
• Data Strategy and Preparation:
• Collaborate with data engineering teams to ensure high-quality data acquisition, preprocessing, and augmentation for model training and fine-tuning.
• Implement data governance and privacy practices in line with organizational policies.
• Innovation and Research:
• Experiment with new generative AI techniques, such as multimodal AI, reinforcement learning with human feedback (RLHF), and active learning.
• Evaluate and recommend AI frameworks, libraries, and platforms for project requirements.
• Stakeholder Collaboration:
• Work closely with product managers, business stakeholders, and UX designers to define AI-powered product features and use cases.
• Present technical concepts, project progress, and AI capabilities to non-technical audiences.

Key Requirements

• Technical Skills:
• Hands-on experience with cloud platforms and services for AI/ML, such as Azure AI Services, Azure Machine Learning, AWS Bedrock, or Google Vertex AI.
• Hands on experience in any of LLMs such as OpenAI’s ChatGPT Models , Gemini, Llama 2 ,Claude 2 ,Grok
• Hands on experience in any of the agentic frameworks like LangChain, Semantic kernel, AutoGen, CrewAi
• Hands on experience using any of vector database like Chroma, Pinecone, Weaviate, Faiss
• Experience with multimodal AI and advanced techniques like Tree-of-Thoughts, Retrieval-Augmented Generation (RAG), or Reinforcement Learning with Human Feedback (RLHF)
• Strong expertise in LLMs and generative AI frameworks like OpenAI, Hugging Face Transformers, or similar platforms.
• Deep understanding of natural language processing (NLP) concepts, including tokenization, embeddings, and sequence-to-sequence models.
• Proficiency in Python and libraries such as TensorFlow, PyTorch, and Scikit-learn.
• Experience in CI/CD pipeline management and automation tools, particularly within the Azure DevOps environment. Knowledge of containerization (e.g., Docker) and orchestration tools is also important
• Familiarity with MLOps tools and practices, such as MLflow, Kubeflow, or Docker.

Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field (Ph.D. preferred).
• 8+ years of experience in AI/ML engineering, with 2+ years specifically in Generative AI.
• Minimum of 2 years of experience in building Conversational AI applications using cloud-based services and in orchestrating AI/ML services for building a complete solution
• Minimum of 6 years of extensive full-time experience in Data Analysis, Statistics, Machine Learning, or Computer Science
• Proven track record of leading AI projects from inception to production.
• Experience with multimodal AI and advanced techniques like Tree-of-Thoughts, Retrieval-Augmented Generation (RAG), or Reinforcement Learning with Human Feedback (RLHF).
• Certifications in AI/ML or cloud platforms (e.g., Azure AI Engineer, AWS Certified Machine Learning).

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.

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.