Top Machine Learning Jobs in India

Design, develop, and deploy machine learning models. Prepare and preprocess large datasets, train and evaluate models, perform hyperparameter tuning and cross-validation, and collaborate with cross-functional teams to translate business requirements into AI/ML solutions. Contribute to design reviews, present findings to stakeholders, and maintain BI tools, dashboards, and model productionization under manager guidance.

Lead analytics for promotions and incentives strategy, building scalable frameworks to measure promo ROI, automate performance tracking, and apply advanced analytics/ML for segmentation, targeting, and impact measurement. Analyze seller behavior and inventory patterns, partner with cross-functional teams, and translate insights into actionable business strategies to optimize pricing and promotions at scale.

Lead research for personalized recommendations at eBay, develop advanced AI models, work with large datasets, and publish findings.

The Product Technical Lead at Airbus guides a team in designing and executing digital product development, focusing on AI/ML, data engineering, and the overall data strategy. Responsibilities include leading LLM development, ensuring code quality, and implementing CI/CD pipelines.

Lead AI/ML engineering vision and roadmap for healthcare and life sciences. Oversee multiple client engagements, design and deploy scalable production-grade AI solutions (ML, NLP, deep learning, computer vision, LLMs), ensure regulatory readiness, responsible AI practices, and drive adoption and value realization while managing executive client relationships and expanding AI adoption.

Lead and grow a backend engineering team building scalable, cloud-agnostic infrastructure and services for big data and ML workloads. Hire engineers, enforce technical standards, partner with product and customers, define roadmap, and coordinate cross-team execution to deliver reliable, monitored, and tested systems at scale.

Design, maintain, and execute manual and automated UI tests (Playwright/TypeScript); perform defect analysis and root-cause investigations; validate databases with SQL; integrate tests into CI/CD (Azure DevOps); apply AI/ML techniques to testing; participate in Agile ceremonies and ensure end-to-end quality for scientific and healthcare products.

Design, build and deliver enterprise BI data products: ingest/transform data, develop scalable data models and ETL/ELT pipelines, and create high-performance Tableau dashboards. Optimize performance, ensure data governance and quality, enable analytics and ML operationalization, automate reporting, and collaborate with cross-functional stakeholders to translate business requirements into production-ready analytical solutions.

Support marketing analytics by implementing machine learning models, automating reporting and model scoring, validating models with NY counterparts, translating business requirements, and streamlining analytics processes using Python, SQL and cloud platforms.

Build end-to-end machine learning solutions for business stakeholders using advanced ML and statistical methods. Work with big data (Spark/PySpark, SQL), AWS, and collaborate with cross-functional teams to validate models, demonstrate value, and deploy scalable analytics, with a product mindset and agile delivery.

Lead design, development, and support of enterprise automation solutions using Automation Anywhere, Power Platform, and Pega. Act as Automation Anywhere SME, create PDDs/SDDs, ensure secure scalable architecture and governance, manage scrum delivery, resolve production issues, and evaluate cognitive automation and ML innovations.

Analyze e-commerce, finance, growth, and operational performance to deliver actionable insights. Build forecasting and predictive models, evaluate projects and KPIs, support stakeholder decision-making, and foster a data-driven culture to improve business performance across departments.

Lead end-to-end data science projects by developing and implementing advanced machine learning and statistical models, translating business needs into analytical solutions, mentoring junior data scientists, and driving methodological innovation to deliver high-quality, actionable insights.

Develop and optimize deep learning, graph, and ML techniques for GPU architectures; work with customers to deliver AI solutions; collaborate with architecture, research, libraries, and system software teams.

Lead presales Solution Architect for UiPath Intelligent Automation. Run discovery workshops, design scalable enterprise automation, deliver demos/PoCs, produce technical proposals, define governance and integrations, and mentor teams while driving CoE and adoption.

Design and build discrete-event, continuous/rate-based, and agent-based AnyLogic models of flexible pipe production to analyze bottlenecks, utilization, WIP, storage, downtime, and throughput. Produce scenarios, dashboards, and reports, integrate models with ML, collaborate with production, engineering, and supply chain teams, maintain models, and support capacity planning and optimization with international collaboration and travel.

Design and implement scalable AI/ML and data-driven cloud or Kubernetes solutions. Build data and model pipelines, integrate enterprise CRMs, operationalize models with dev teams, manage stakeholders, and support CRM-driven and agentic AI use cases across concurrent projects.

Lead development of cross-site capacity and scheduling models, perform operations research and statistical analyses, design predictive and optimization algorithms, reduce cycle time and optimize WIP, standardize industrial engineering practices, mentor junior engineers, and support capacity planning and fab expansion across manufacturing sites.

Lead cross-site capacity modeling, scheduling, and productivity initiatives for front-end semiconductor manufacturing. Develop analytical and optimization tools, apply operations research and Factory Physics to reduce cycle time and optimize WIP, validate scheduling logic, mentor junior engineers, and partner with operations, supply chain, and IT to support capacity planning and fab expansion.

Support design, integration, verification, and testing of hardware, software, and systems. Develop and execute test plans and automated scripts, report defects, build AI-assisted verification frameworks, create data pipelines and dashboards, and maintain test environments for optical networking platforms.

Build and own backend services for millions of MAUs, design scalable systems, and ship production AI/ML features (voice agents, chat, recommendation and memory engines). Automate key workflows and operate end-to-end ownership of services and stacks.

Lead design, build, and optimize scalable data integrations and platforms using OIC and GCP. Develop ETL/ELT pipelines, manage APIs, ensure data quality, troubleshoot integrations, collaborate with stakeholders, document solutions, and apply best practices for secure, analytics-ready data.

Technical lead responsible for designing and delivering enterprise web and mobile features, owning features end-to-end, leading and mentoring a distributed engineering team, influencing product design, implementing ML/NLP solutions, and ensuring compliance with performance, privacy, and security requirements.

Conduct assessments in sales, marketing, and supply chain; analyze data to identify trends and solutions; collaborate globally to drive revenue and innovate solutions.

Manage client relationships, develop technology solutions, oversee project delivery, and lead a cross-functional team. Focus on business development and talent retention.