Top Machine Learning Jobs in India

As a Staff Data Scientist, lead complex data science projects, define analytical frameworks, and mentor team members to improve healthcare outcomes using advanced models.

Lead product strategy and execution for the Enterprise Data Platform's Unstructured Data domain. Define roadmap, manage end-to-end product lifecycle, partner with engineering and UX, drive adoption and go-to-market, measure performance with KPIs, and mentor product managers in a scaled agile, global environment.

Lead a team building user-facing product features that leverage the ML platform. Design scalable, reliable frameworks and APIs, develop full-stack features, resolve production issues, ensure performance and security, and collaborate across teams while participating in code and design reviews.

Lead a Core Platform engineering team to design and build scalable, reliable backend and API product features that integrate with ML systems. Drive service-oriented architecture evolution, implement frameworks for rapid feature development and deployment, resolve production issues, participate in code/design reviews, and support continuous delivery in a high-concurrency environment.

Lead and grow a data science team to deliver predictive and ML-driven insights. Partner with business and engineering to build production-ready models, enforce model governance, ensure explainability, and measure business impact while driving continuous improvement.

Design and implement scalable backend services, lead full software lifecycle, write design docs, mentor engineers, collaborate cross-functionally, improve performance and quality, and integrate AI tools to boost development productivity.

Lead technical design and build scalable data pipelines and platforms to support AI Ops, SRE, and analytics. Set standards for quality, security, and observability, mentor engineers, operationalize models, and contribute to roadmap and documentation for the ONE Data Lake.

Serve as primary customer contact for FourKites' SaaS platform: troubleshoot, replicate, and track product issues; coordinate with Development, QA, and Consulting; provide regular client updates; participate in weekend emergency rotation; and contribute to AI-driven support initiatives.

Develop and improve digital products using .NET Core and related frameworks. Implement features, fix issues, collaborate with global product teams, research solutions, and follow development best practices.

Work in a cross-functional team to develop, implement, and apply numerical and multi-physics models for materials, structures, and processes supporting memory development. Use scientific computing, computational materials methodologies, and ML techniques to analyze results, report findings, and collaborate on next steps. Position is temporary (up to 12 months).

Develop and implement numerical and computational models (structure, materials, process) to support DRAM and NAND node development. Collaborate with process and product teams, create modeling tools and algorithms, analyze results, and present insights to engineering teams and leaders for silicon implementation.

Lead product strategy and roadmaps for data science, ML, and cloud products in healthcare. Translate business needs into technical requirements and user stories, drive Agile delivery, analyze user and market data to set metrics, design and deploy AI-powered solutions responsibly, mentor junior PMs, and ensure compliance with healthcare regulations throughout the product lifecycle.

Lead end-to-end product lifecycle for healthcare-focused data science, cloud, and analytics products. Define strategy, prioritize backlog, translate business needs into technical requirements, collaborate with engineering and data science to design and deploy AI/ML solutions, support launches, and measure product performance.

Lead design and implementation of an Analytic Foundation and scalable big-data services delivered via APIs. Build data pipelines, analytics and data models, responsive UIs, and production ML/data-driven applications. Ensure high-quality, well-tested code, mentor junior engineers, drive process improvements, and collaborate with product and design teams to deliver customer-focused data solutions.

Lead design and adoption of cloud-native architecture and AI-enabled engineering across Asset & Wealth Management. Advise on technology selection, create scalable reusable frameworks, develop and review secure production code, set multi-year roadmaps, and establish governance and guardrails for agentic AI, automation, and responsible AI use at scale.

Lead analytics strategy and advanced modeling for Zynga games. Solve ambiguous, high-impact problems, build scalable measurement and ML systems, influence executive decisions, mentor analysts, and drive data-informed product and studio-wide impact through rigorous experimentation and reproducible analytics.

Designs and maintains automated tests for front-end, middleware, database, connectivity, and embedded systems. Develops AI- and LLM-integrated automation workflows, performs endurance and stability testing, validates releases, manages defects, repairs complex scripts, and conducts peer reviews. Partners with software engineers, reports results to leadership, supports risk-based testing and release readiness, and may lead projects or teams in a global delivery environment.

Lead technical design and delivery of production AI platforms: representation learning, embeddings, vector search, multimodal and agentic AI, LLM-based systems, and geospatial solutions. Architect scalable, explainable production ML systems, set best practices, mentor engineers, measure business impact, and drive research and innovation.

Lead and manage AI/ML engineering teams to design, build, deploy, and operate AI and Generative AI solutions across healthcare domains. Drive technical strategy, mentor engineers, ensure code quality and DevSecOps automation, collaborate with stakeholders, and deliver production-ready ML systems using modern frameworks, cloud platforms, and best practices.

Design, develop, and deploy production-grade ML and deep learning models across healthcare use cases. Analyze large datasets, perform feature engineering, validate models, ensure governance and explainability, collaborate with data engineering, and communicate results to technical and nontechnical stakeholders while applying healthcare data standards and synthetic data techniques.

Design, build, and deploy AI-driven observability solutions. Develop LLM/NLP and generative AI features (RAG, semantic search, embeddings) for incident reports, root-cause analysis, and remediation guidance. Optimize models for real-time, cloud-native deployment (AWS/GCP, Kubernetes), and collaborate with product, platform, and engineering teams to integrate AI capabilities across the LogicMonitor platform.

Design and implement a unified orchestration layer coordinating vendor and internal LLMs and human agents. Build production-grade Python services, drive ML projects from design to delivery, ensure secure, scalable AI-enabled customer experiences, and collaborate across teams to meet security, compliance, and performance standards.

Designs and deploys predictive machine learning, advanced analytics, Generative AI, and agentic LLM solutions for banking control-management workflows. Builds reusable agent frameworks, production ML pipelines, monitoring and evaluation systems, and workflow automation supporting risk, regulatory change, controls, issue management, governance, and reporting. Partners with product, engineering, and risk stakeholders to define requirements, measure outcomes, ensure responsible AI practices, and scale reliable services across Consumer and Community Banking.

Designs, develops, deploys, and optimizes responsible AI-powered software solutions. Evaluates emerging AI frameworks and developer tools, collaborates with engineering, product, and business teams, participates in architecture and security reviews, troubleshoots complex systems, and mentors junior engineers.

Lead design and delivery of scalable, cloud-native AI and data platforms on Azure. Architect and implement generative AI/LLM/RAG solutions, optimize Spark/Databricks performance, guide teams, enforce standards, and collaborate with stakeholders to drive enterprise AI adoption in healthcare.