Top Machine Learning Jobs in India

Lead data and analytics strategy for Global Stores, defining architecture and roadmaps, delivering scalable data platforms and AI solutions (Gen AI/Agentic AI), driving cross-functional delivery, ensuring data quality/security, and mentoring engineering teams.

Leads enterprise detection engineering across SIEM, EDR, NDR, cloud, on-premises, and OT/ICS environments. Owns detection strategy, content development, MITRE ATT&CK coverage, platform tuning, automation, detection-as-code, quality standards, and performance metrics. Partners with SOC, incident response, threat intelligence, offensive security, engineering teams, and vendors to validate detections, reduce false positives, close coverage gaps, and improve time-to-detect.

Leads technical partnerships with system integrators and cloud providers, developing generative AI solutions, reference architectures, and deployment best practices. Supports strategic customer deals, enables partner AI practices, troubleshoots complex issues, presents at technical events, gathers product feedback, and informs Anthropic’s roadmap and go-to-market strategy.

Develops hardware-accelerated AI software for multimedia platforms, including audio, video, augmented reality, computer vision, and streaming applications. Responsibilities include designing algorithms, deploying applications across platforms, profiling and optimizing AI pipelines, addressing system-level resource challenges, and writing Python and C++ code. Requires substantial Linux software development experience, cloud-native architecture knowledge, and expertise in computer vision, machine learning, and deep learning.

Design and scale observability and reliability frameworks using metrics, logs, traces, predictive analytics, anomaly detection, and machine learning. Establish dashboards, SLAs, SLOs, SLIs, and high-availability architecture for distributed systems. Develop AIOps capabilities for root-cause analysis, predictive capacity planning, alert deduplication, and noise reduction. Mentor engineering teams and communicate complex technical concepts to leadership.

Leads global Quality, Operations, and Continuous Improvement platforms, analytics, AI transformation, governance, and operational excellence. Owns product roadmaps, Agile delivery, platform adoption, business cases, ROI, stakeholder alignment, and enterprise-scale improvement initiatives across manufacturing and business units.

Owns account management, revenue targets, client relationships, and media growth for key advertising accounts in India. Drives cross-selling, upselling, campaign optimization, issue resolution, and strategic client conversations. Coordinates Sales, Product, Ad Operations, Engineering, Finance, Legal, Marketing, and other teams while providing data-driven insights and feedback on product and market needs.

Leads omnichannel customer engagement measurement and advanced analytics across pharmaceutical HCP and patient touchpoints. Performs attribution, causal inference, machine learning, experimentation, dashboarding, and campaign performance analysis. Translates analytical findings into commercial recommendations, partners with cross-functional stakeholders, mentors analysts, and develops reproducible, governed measurement frameworks and automated workflows.

Leads global Finance Transformation programs, including AI and automation initiatives from use-case identification through deployment and scaling. Responsibilities include program planning, governance, budgeting, risk management, stakeholder communication, financial reporting, AI governance, compliance, change management, and benefits realization. Partners with Finance, Technology, Data, Procurement, Legal, Risk, vendors, and senior leadership to deliver measurable improvements across finance processes.

Build modular, API-first internal product creation tools for Nike using cloud-native software engineering. Develop modern web applications and backend services, collaborate with product managers and principal engineers, apply architectural patterns, testing practices, CI/CD, infrastructure as code, AWS services, and frontend technologies. Support scalable tools for Nike’s Innovation and Consumer Creation teams, with opportunities to integrate AI and machine learning solutions.

Lead large-scale enterprise AI transformation programs from strategy through implementation. Responsibilities include defining delivery roadmaps and governance, managing global cross-functional teams, overseeing budgets and risks, partnering with executives and clients, supporting proposals, driving Responsible AI adoption, and mentoring delivery leaders. The role requires extensive experience delivering AI, Generative AI, Agentic AI, Machine Learning, and AI/ML platform solutions across cloud environments.

Own the technical roadmap for Material Master data stewardship platforms, including Syniti DSP integrations with SAP ECC and SAP S/4HANA. Lead data governance, workflow redesign, automation, AI adoption, release management, GxP compliance, validation, audit traceability, and global stakeholder collaboration. Translate business requirements into technical specifications, prioritize backlogs, oversee UAT, and mentor teams in automation and digital practices.

Leads technology and AI strategy for a client account, developing roadmaps, governance frameworks, predictive models, intelligent dashboards, and data-driven performance management. Oversees BI, data science, data quality, reporting automation, and AI solution deployment. Advises clients and internal stakeholders, manages complex technology initiatives, and drives measurable improvements in efficiency, cost savings, predictive accuracy, and client satisfaction.

Lead enterprise AI initiatives from discovery through deployment, translating business requirements into technical roadmaps and delivering scalable software solutions. Collaborate with product, engineering, and data science teams in agile environments, lead technical assignments, manage stakeholders, promote secure coding and testing practices, and navigate governance requirements in a regulated environment.

Develop proofs of concept and production-oriented data science and AI solutions for government and organizational clients. Responsibilities include identifying use cases, preparing and assessing data, statistical modeling, forecasting, machine learning, LLM prototyping, evaluation, documentation, stakeholder communication, and client delivery. The role will establish data science capabilities for ICF’s India team and contribute to proposals, reusable processes, and project implementation.

Designs scalable architectures for automation frameworks, engineering tools, and intelligent systems. Leads architectural decisions, evaluates emerging technologies, develops prototypes, and guides teams toward production-ready solutions. Responsibilities include architecture reviews, technical standards, performance and reliability optimization, mentoring engineers, and collaboration with global stakeholders. The role also supports AI, generative AI, machine learning, distributed systems, and technology roadmaps across Ubisoft studios.

Leads enterprise AI/ML and mathematical optimization initiatives across healthcare, including solution architecture, hybrid ML-optimization modeling, generative and quantum-inspired AI, solver integration, MLOps, governance, and production deployment. Develops prototypes and reusable frameworks, guides technology adoption, mentors engineers, leads small teams, and partners with business, product, architecture, and engineering stakeholders to deliver scalable, compliant optimization solutions.

Leads enterprise AI strategy, architecture, and production delivery across generative, agentic, and classical machine learning. Designs LLM, RAG, orchestration, predictive, and advanced analytics solutions for healthcare and pharmacy operations. Establishes MLOps, LLMOps, governance, safety, monitoring, and evaluation frameworks while partnering with executives, product, engineering, and platform teams. Mentors technical practitioners and drives reusable AI standards, services, and accelerators.

Lead full-chip floor planning, custom analog and mixed-signal layout, physical implementation, verification signoff, and tape-out for advanced memory and high-speed interface designs. Own DRC, LVS, ERC, EMIR, reliability, and manufacturability closure. Define scalable layout methodologies, drive AI-enabled design automation, lead global cross-functional teams, mentor engineers, and deliver advanced-node semiconductor products.

Develops and supports machine-learning and advanced analytics solutions for Blue Yonder’s Luminate Planning suite. Responsibilities include feature selection, model development and evaluation, data mining, data cleansing, statistical analysis, forecasting validation, API and workflow integrations, and stakeholder presentations. The role also addresses customer data and forecasting concerns, mentors junior team members, and collaborates globally across implementation, product, support, and customer teams.

Build and validate rapid GenAI, VLM, and machine learning prototypes for game testing and quality control. Design experiments, develop data pipelines, evaluate model performance, integrate prototypes with internal tools, analyze failure modes, and document reproducible research practices. Collaborate in agile workflows with R&D and cross-functional teams while gaining experience in software development, testing, automation, CI/CD, and gaming technologies.

Design, develop, and maintain enterprise-grade full-stack/backend systems; ship production-quality code to production; interact with customers and industry leaders to shape product direction; solve complex AI-native problems in the insurance money-movement domain. Requires strong CS fundamentals, analytic problem-solving, ownership mindset, and 4+ years experience.

Designs, develops, tests, and deploys machine learning models and workflows for audience measurement. Builds data pipelines using Databricks and AWS S3, cleans complex data sources, applies statistical and econometric methods, and maintains production-quality Python, PySpark, and SQL code. Creates Tableau visualizations, communicates research findings, and collaborates with Engineering, Product, Data Science, and Technology stakeholders to deliver data-driven improvements.

Maintains, optimizes, and supports enterprise applications and infrastructure. Troubleshoots application issues, implements software deployments and configuration changes, supports onboarding and decommissioning, and contributes to systems recovery. Configures packaged software, develops modification and interface requirements, coordinates solutions with technical teams and vendors, executes change requests, mentors junior staff, and provides strategic recommendations.

Develop machine learning prediction models across customer acquisition, behavior, collections, marketing, fraud, and propensity use cases. Design data-driven strategies for banking products, leverage digital and alternative data, collaborate with external data providers, and lead large-scale model development and deployment. Own the full machine learning lifecycle, including feature engineering, training, validation, documentation, deployment, monitoring, and feedback loops.