Top Machine Learning Jobs in India

Own Capital One’s corporate communications and technology employer brand in India. Responsibilities include media relations, PR, technology content, event and sponsorship execution, agency management, executive spokesperson preparation, crisis communications, and brand governance. The role builds Capital One’s reputation as a technology leader and attracts engineering and data science talent through external and internal communications.

Lead AI, machine learning, and generative AI strategy and engineering for marketing-related domains. Design, deploy, and scale solutions using LLMs, RAG, AI agents, vector databases, and model fine-tuning across AWS, Azure, and GCP. Drive AI lifecycle automation through Agile, DevSecOps, and CI/CD practices; mentor teams; establish engineering standards and governance; and integrate AI capabilities into enterprise products and platforms.

Leads AI strategy and adoption for Wholesale Lending Services by developing AI roadmaps, integrating AI capabilities into products, architecting agentic workflows, and advancing prompt engineering. Designs AI training programs, establishes adoption and business-impact metrics, monitors outcomes, advises senior leaders, and serves as an internal AI subject matter expert. The role requires cross-functional leadership, stakeholder influence, and experience delivering AI-powered products.

Validate and document complex commercial credit, corporate economic, and model risk models. Analyze forecasting, regression, machine learning, stress testing, backtesting, sensitivity, and scenario methodologies. Assess data integrity, model performance, implementation, monitoring, and regulatory compliance. Produce validation reports, identify model risks, calculate losses and capital requirements, and communicate findings to developers, auditors, regulators, and business stakeholders.

Leads data engineering teams and provides technical direction for scalable, reliable data platforms and solutions. Oversees Agile delivery, backlog planning, operational support, quality standards, technical debt reduction, and stakeholder communication. Coaches engineers, sets performance goals, drives innovation, and guides adoption of data, cloud, containerization, DevOps, artificial intelligence, and machine learning technologies.

Build and operate scalable machine learning services for Expedia Group’s advertising platform. Responsibilities include designing ML systems and APIs, productionizing models, developing testing and observability tooling, managing data preparation through deployment and monitoring, responding to incidents, and improving reliability, performance, security, and cost efficiency. The role collaborates with product managers, data scientists, architects, and engineers while contributing to responsible AI practices and ML platform evolution.

Designs, develops, maintains, and improves scalable software applications and systems. Leads AI adoption across software deployment automation, collaborates with product and engineering teams, troubleshoots complex issues, participates in code reviews, and documents applications and deployment processes. Creates training, demonstrations, workshops, playbooks, reusable patterns, and use cases to help engineering teams and business stakeholders adopt AI solutions.

Architects scalable ETL/ELT pipelines and enterprise lakehouse architectures; develops predictive machine learning models and production Generative AI, multi-agent, and RAG systems. Processes petabyte-scale data with Python, Scala, PySpark, Spark, and advanced SQL. Builds reusable features, optimizes distributed workloads, and applies software-engineering practices including testing, scalability, data quality, and continuous integration. Collaborates with research, engineering, and product teams while embedding ethical AI principles.

Design, implement, optimize, and deploy machine-learning and computer-vision systems for AI dashcams and fleet safety. Evaluate production models, develop ML modules, debug algorithm failures, optimize models for real-time embedded performance, and build training, validation, deployment, model compression, and active-learning pipelines. Collaborate with embedded, backend, frontend, hardware, QA, and AI teams while supporting large-scale ML infrastructure.

Lead end-to-end delivery of large, complex technical epics and engineering initiatives. Manage engineering teams, dependencies, risks, milestones, releases, governance, and stakeholder communications. Partner with engineering, architecture, product, business, and delivery teams to ensure predictable, high-quality outcomes. Facilitate Agile practices, resolve impediments, establish accountability, and translate technical information into business insights. Experience delivering AI, machine learning, cloud, data, API, or enterprise-scale initiatives is advantageous.

Senior Product Manager responsible for defining and delivering shared services for SailPoint’s enterprise identity security platform. The role partners with Product, Design, Engineering, and stakeholders to guide SaaS and cloud capabilities from discovery through launch, prioritize roadmaps, define requirements, track adoption metrics, and shape long-term platform strategy. The position is hybrid in Pune and requires approximately 15% travel.

Leads AI, GenAI, and agentic AI initiatives for marketing analytics and decisioning. Responsibilities include roadmap delivery, ML and GenAI solution development, model deployment and monitoring, marketing measurement, technical team leadership, model governance, risk controls, and stakeholder partnership. Develops propensity, churn, uplift, attribution, segmentation, channel optimization, and experimentation solutions while connecting AI outcomes to customer and business KPIs.

Own digital product vision, roadmap, discovery, requirements, and delivery for AI-enabled automation across the wholesale lending booking lifecycle. Partner with business and technology stakeholders to implement workflow, ML, generative AI, and agentic solutions. Lead Agile delivery, QA/UAT, release readiness, governance, change management, adoption, KPI dashboards, and continuous improvement in a regulated financial-services environment.

Lead the design, implementation, and optimization of mathematical models and production optimization engines for supply chain and strategic sourcing. Formulate MIP, LP, NLP, network flow, and heuristic algorithms; tune commercial solvers; integrate scalable solutions into a multi-tenant SaaS platform; validate model performance; and mentor engineering and research teams. Collaborate with product and engineering leaders to translate business constraints into reliable, production-grade software.

Develop and deploy AI/ML, GenAI, LLM, analytics, and predictive solutions for aerospace applications. Responsibilities include managing the full ML lifecycle, building scalable production models, conducting research and proof-of-concepts, applying advanced statistical and deep learning methods, documenting results, collaborating internationally, and mentoring junior data scientists.

Leads development of secure, scalable software services and applications using Java, Spring, Kafka, APIs, and distributed-system patterns. Owns complex cross-service problems, architecture, prioritization, automation, integration, troubleshooting, incident analysis, and operational excellence. Mentors engineers, guides technical decisions, promotes secure coding and quality practices, partners with product teams, supports agile delivery, and conducts technical interviews.

Leads strategy and execution for Mastercard’s next-generation disputes platform. Owns strategic platform domains, roadmaps, backlogs, product requirements, investment priorities, and outcomes across multiple agile teams. Partners with executives, customers, engineering, architecture, data science, design, and regional stakeholders. Drives AI, automation, predictive decisioning, and generative AI adoption across dispute resolution experiences and operations while coaching product teams and influencing enterprise modernization and portfolio investment decisions.

Develop predictive and prescriptive machine learning models, deploy and monitor them in production, and build scalable data services and MLOps workflows. Analyze complex datasets using Python, Spark SQL, Azure, Databricks, and MLflow; evaluate model performance and data drift; create technical architecture artifacts; conduct cost-benefit analyses; and communicate findings to technical and nontechnical stakeholders.

Leads enterprise reporting, analytics, and data engineering strategy across Azure, AWS, and GCP. Designs scalable data platforms, dashboards, scorecards, self-service analytics, and executive reporting using Databricks, Spark, SQL, Power BI, and modern data technologies. Establishes governance, data quality, security, compliance, and operating standards; drives modernization, automation, AI-assisted analytics, and transformation initiatives. Partners with stakeholders and clients, mentors distributed teams, reviews technical work, and serves as a subject matter expert for reporting, business intelligence, and modern data platforms.

Leads data science, advanced analytics, reporting governance, and AI initiatives. Responsibilities include predictive and statistical modeling, trend analysis, executive reporting, metric standardization, data quality, enterprise reporting architecture, generative AI, conversational analytics, RAG, prompt evaluation, responsible AI, and translating technical insights for senior stakeholders.

Lead a healthcare analytics and clinical configuration team, owning end-to-end auto-decisioning strategies for new client implementations. Translate business needs into scalable analytical frameworks, develop performance tracking and optimization initiatives, and deliver actionable insights from healthcare data. Partner with data governance and cross-functional teams to ensure explainable, responsible analytics. Manage team hiring, mentoring, coaching, and day-to-day operations while influencing product and business outcomes.

Leads quantitative analytics for Consumer and Community Banking, analyzing complex datasets to generate actionable business insights and strategies. Responsibilities include advanced data mining, statistical analysis, visualization, reporting, stakeholder communication, data modeling, data quality assessment, process improvement, and independently managing analytical programs. The role serves as a subject matter expert and partners with business leaders to improve product performance, customer experience, and operational efficiency.

Develop data pipelines, dashboards, AI agents, generative AI capabilities, and scalable model integrations. Use Python, SQL, Databricks, Tableau, and Alteryx to generate actionable insights, monitor model performance, ensure data quality, and support data-driven business decisions on agile teams.

Performs advanced quantitative analysis on complex datasets to develop business strategies, improve product and campaign performance, and deliver actionable insights. Responsibilities include data mining, statistical analysis, visualization, reporting, data quality assessment, anomaly detection, and stakeholder communication. The role serves as a data analytics subject matter expert, contributes to data models and enterprise data strategies, supports process improvement, and independently manages analytical programs and business initiatives.

Leads quantitative analytics for consumer banking campaigns and outreach initiatives. Responsibilities include predictive modeling, forecasting, experimentation, portfolio analysis, business-case development, reporting, data quality assessment, and strategic deep dives. Partners with stakeholders to optimize performance and inform business decisions, manages analytics programs and processes, mentors junior team members, and promotes adoption of data-driven recommendations.