Top Machine Learning Jobs in India

Lead product management for data and analytics solutions in Supply Chain Management. Coordinate with stakeholders, conduct implementation, manage adoption, and enhance solutions based on business needs.

The Staff Software Engineer will develop AI/ML models and solutions, collaborate on design and implementation, and support R&D efforts in the healthcare industry.

Develop and optimize machine learning models for demand forecasting and planning using various AI techniques while collaborating with project teams to ensure successful delivery.

The AI Solutions Engineer role involves deploying AI tools, optimizing AI agents, improving workflows with AI, integrating systems, and training users on AI solutions.

Lead the ML function for InMobi by architecting and building production machine learning systems, optimizing marketing spend, and driving performance in ad-tech.

The Senior Sales Manager drives revenue and customer satisfaction by developing strategic client relationships and delivering customized advertising solutions. They manage client activities and ensure clients' advertising needs are met through effective engagement and planning.

The Senior Talent Development Partner will lead talent systems across InMobi, focusing on performance management, leadership development, and career architecture to foster growth and drive impactful talent experiences.

Develop applications using AI and ML techniques, focusing on generative AI models, deep learning, and cloud-based solutions while collaborating with cross-functional teams.

Develop AI applications using Machine Learning and Generative AI. Collaborate across teams, conduct research, optimize models, and ensure data quality.

Partner with FP&A to perform GL-level variance analysis, deliver daily/monthly reporting, drive automation and standardization, maintain SOPs, lead training, manage client queries, and design/implement AI/ML and Generative AI solutions integrated with Power BI, Alteryx, and SQL pipelines in collaboration with tech and data teams.

Lead R&D and deliver end-to-end LLM/ML solutions for text extraction, analysis and recommendation engines. Develop, fine-tune, and deploy ML/LLM models for matching customers with relevant content, ensure scalable cloud integration (AWS), collaborate with engineering and product, communicate results via visualizations/reports, and mentor junior engineers to drive continuous improvement and measurable business outcomes.

Lead Six Sigma (Black Belt) projects using DMAIC to drive quality, efficiency, cost reduction, and improved customer experience. Manage cross-functional initiatives, run deep-dive workshops, perform statistical analysis, deliver findings for decisions, coach/train belts, and drive sustainable change across the organization.

Lead and manage a team of AI/ML professionals to develop and deploy ML solutions. Define AI strategy, oversee projects from conception to production, provide technical leadership, evaluate new technologies, collaborate with stakeholders, and ensure ethical, secure data practices and timely delivery.

The Compliance Operation Analyst performs screening of transactions, ensures adherence to trade regulations, and provides expertise on compliance operations, using data analytics to enhance performance and efficiency.

Designs and builds production-grade AI/ML and GenAI cloud solutions across the full ML lifecycle. Architects scalable GenAI, Agentic AI, RAG/GraphRAG, vector retrieval and knowledge-graph systems; leads MLOps/LLMOps, observability, governance, and cloud deployments; mentors engineers, drives platform standards, and integrates emerging AI technologies to ensure secure, reliable, and scalable AI services.

Lead product strategy and execution for Communications within Lending. Define OKRs and roadmaps, collaborate with engineering, design, ML, risk and compliance, use data to drive decisions, and deliver omni-channel communication features that improve members' financial health.

Lead technical engagements to architect, deploy, optimize, and scale production AI and agentic systems on DigitalOcean's AI-Native Cloud. Build benchmarking, automation, deployment frameworks, and playbooks. Validate platform capabilities, surface operational insights, and collaborate with customers, vendors, and internal teams to accelerate adoption and improve platform reliability, performance, and cost-efficiency.

Lead deployment, optimization, and scaling of production AI and agentic systems on DigitalOcean's AI-native cloud. Work across inference engines, runtimes, orchestration, and GPU infrastructure to benchmark, tune, and automate deployments; act as early customer validator and build reusable deployment frameworks, tooling, and enablement assets while collaborating with customers, partners, and internal product and engineering teams.

Lead data stewardship for CDD/financial crime data: investigate data quality, lineage, and controls; design ETL pipelines; apply advanced analytics and ML to large datasets; build dashboards and automated reports; translate insights into actionable business and compliance recommendations; advise stakeholders and support governance, risk mitigation, and regulatory readiness.

Design, build, and operationalize ML and deep learning solutions including supervised/unsupervised models and LLM fine-tuning. Implement RAG, vector DBs, prompt engineering, deploy on cloud (AWS/Azure), set up experiments, and present technical findings while partnering with business stakeholders.

Intern will develop and enhance software supporting asset management (trading, research, data tools), perform code reviews and maintenance, leverage AI/ML, big data, and cloud technologies, collaborate cross-functionally, document and present work, and engage with senior professionals in a fast-paced hedge fund environment.

Participate in software engineering projects supporting trading, research, and data tools. Develop and maintain code, perform code reviews, work with AI/ML, big data, and cloud technologies, collaborate with cross-functional teams, document designs, and learn hedge fund industry practices under senior mentorship.

Participate in software development for asset management tools, perform code reviews, maintain codebases, apply AI/ML, big data and cloud solutions, collaborate with cross-functional teams, document and present technical work, and learn industry best practices under senior mentorship.

Execute independent technology and cybersecurity control testing across SDLC, cloud (Azure/AWS), access control, encryption, endpoint, network, logging, incident response, and vulnerability management. Assess control design and effectiveness, document findings (Risk & Control Matrices), collaborate with business and risk teams to remediate gaps, and report results to management.

Partner with business units to implement data and records governance, ensure data quality and lineage, monitor metrics, drive remediation and controls, support regulatory reporting, and deliver data-driven improvements across BAU and change programs.