Top Machine Learning Jobs in India

Analyze large-scale transactional, operational, and customer datasets; build visualizations, machine learning models, and experiments; translate complex findings into clear recommendations for operational teams and executives; and apply analytical software, databases, visualization tools, and programming languages in a fast-paced blockchain environment.

The Group Product Manager will define strategies and lead the development of AI-driven product knowledge systems, enhance search and recommendation features, and collaborate cross-functionally to drive data-informed decisions.

Leads the strategy, design, governance, and support of enterprise Finance data products. Owns discovery, roadmaps, requirements, prioritization, data quality controls, reconciliation, exception management, stakeholder communication, and continuous improvement. Partners with Finance, IT, data engineering, analytics teams, and vendors to deliver reliable data products across platforms, dashboards, APIs, semantic layers, and ML-enabled solutions. Guides support resources and drives complex issues to permanent resolution.

Build scalable backend platform capabilities, infrastructure, tooling, and ML frameworks for Walmart’s Membership Experience Engineering team. Lead the full software development lifecycle, apply cloud-native architecture, design APIs and resilient systems, integrate AI and machine learning components, conduct design reviews, and ensure deployment, observability, and maintenance. Mentor engineers, influence technical decisions, collaborate with stakeholders, and use data-driven practices to improve engineering productivity and product outcomes.

Lead and grow a Physical Design Methodology & CAD team in India to define RTL-to-GDSII flows, automation, sign-off solutions, and AI-driven CAD transformations. Partner globally with architecture, design, verification, infrastructure, and EDA vendors to deliver scalable SoC/ASIC development, improve productivity, quality, and time-to-market.

Lead patient services analytics across hub services, specialty pharmacy, copay assistance, prior authorization, appeals, and claims. Apply advanced analytics and data science to identify access barriers, improve therapy initiation and adherence, and support commercialization strategies. Develop dashboards, KPI reporting, and actionable recommendations for market access and commercial leadership. Partner with clients, vendors, specialty pharmacies, and cross-functional teams while ensuring data quality, governance, and effective stakeholder communication.

Work with Product, Business, and Engineering to collect, clean, analyze data, build Python and SQL automation, contribute to internal analytics platforms, assist cloud deployments, and document technical solutions to support decision-making.

Lead product vision, strategy, and execution for a chat-first enterprise platform. Collaborate with data scientists, ML engineers, and designers to build conversational AI features, curate datasets, implement benchmarking and training workflows, define KPIs, and drive data-driven product optimization for enterprise workflow automation.

Leads Android software development across design, coding, testing, deployment, debugging, and production support. Develops scalable and secure mobile solutions using Kotlin and modern architectures, integrates AI and ML capabilities, conducts code reviews, supports CI/CD and DevOps activities, monitors performance, and promotes engineering best practices. Collaborates with cross-functional teams, owns feature delivery, mentors peers, and contributes to Walmart+ customer-focused platform improvements.

Lead client discovery and consult on technical/business needs, develop proposals and solution decks, collaborate on high-level architecture with solution architects, research Cloud/Data/GenAI trends, and coordinate across sales and delivery for successful pre-sales engagement.

Lead and scale engineering teams to build massively scalable software and systems; architect low-latency infrastructure; proactively guard against cyber threats; apply machine learning and financial engineering to turn data into action in a fast-paced global environment.

Apply AI/ML, data engineering and advanced analytics to solve client business problems across industries. Structure problems, develop hypotheses and models, generate insights for functional decisions, contribute to IP and modeling R&D, present recommendations, and support implementation using tools like SAS, Python, R, Tableau and Power BI.

Design and deliver AI-ready technical documentation and information experiences for Guidewire's cloud platform, applications, services, and APIs. Collaborate with engineers, product managers, and designers to create structured content, taxonomies, and metadata; use analytics and AI tools to identify gaps and improve content; and own documentation for product areas to support fast releases and improved customer self-service.

Lead strategy and execution for intelligent finance and grantmaking products. Translate nonprofit accounting and grantmaking domain knowledge into product requirements, manage agile delivery and backlogs, partner with engineering and design, and drive AI-enabled innovations to improve financial workflows and user experience.

Lead advanced statistical analyses and machine learning projects, partner with cross-functional teams to design data-driven solutions, manage large datasets with governance best practices, build predictive models to forecast trends, and communicate insights to stakeholders.

Support and contribute to Data Solutions product management: handle product requests, assist in product design, analyze recurring issues and metrics, create support documentation, and share best practices while collaborating with content, product, sales, and engineering teams.

Design, develop, and optimize secure, scalable cloud data platforms and ETL/ELT pipelines across AWS, Azure, and GCP. Write Python and SQL, implement data governance and quality controls, optimize performance and costs, and support analytics and BI layers. Contribute to architecture, pre-sales demos, proofs of concept, and client discussions. Mentor junior developers, conduct code reviews, and collaborate with architects, QA, DevOps, and business stakeholders.

Supports AI and analytics discovery by analyzing operational data and process flows, identifying inefficiencies, assessing AI/ML use cases, and generating business insights. Responsibilities include data exploration, analytical modeling, process mining, dashboard and visualization development, data-readiness assessment, documentation of assumptions and limitations, and collaboration with data scientists, business analysts, consultants, and architects. Healthcare domain experience is required.

Analyze and solve complex problems using AI, build and industrialize end-to-end AI assets, and drive innovation through patents and publications. Lead, mentor, and guide teams while developing machine learning, deep learning, NLP, and LLM solutions using cloud and open-source technologies. Establish client relationships, manage stakeholders, understand business challenges, and deliver business impact. Rotational shifts may be required.

Develop, calibrate, monitor and automate counterparty risk models and analyses; attribute P&L to risk factors; prototype risk models; build quantitative tools; produce industry trend reports and support stress testing for reporting and event response.

Design, develop, and deploy advanced AI, generative AI, and agentic systems at enterprise scale. Build multi-agent architectures with orchestration, retrieval, memory, guardrails, evaluation, and human review. Develop end-to-end ML pipelines, RAG solutions, deep learning applications, and LLM prompt optimization. Own engineering deliverables from requirements through post-release support, conduct large-scale experiments, and provide statistical insights while collaborating with engineering, architecture, and business stakeholders.

Lead site-level process excellence and continuous improvement initiatives using LSS; drive customer experience and operational metrics, identify automation opportunities, coach teams, and liaise with stakeholders to deliver transformational value.

Provides engineering-led support for enterprise Azure customers, resolving complex and critical cloud issues, conducting root-cause analysis, optimizing deployments, and managing escalations. Partners with engineering, product, field, and support teams to improve reliability, customer health, troubleshooting guidance, and platform capabilities. Acts as the customer advocate by translating usage patterns and feedback into actionable product and service improvements.

Serves as the primary engineering and support contact for Azure customers, resolving complex escalations and mission-critical issues. Performs root-cause analysis, health checks, configuration and deployment guidance, and impact analysis. Uses telemetry and customer feedback to identify product defects, improve troubleshooting content, and influence Azure engineering priorities. Collaborates with account managers, architects, support teams, product groups, and software engineers to improve reliability, customer health, and the Azure support experience.

Lead architecture and delivery of enterprise AI and data platform solutions on Azure. Drive GenAI/LLM, RAG, and Databricks implementations, enforce engineering standards, perform architecture reviews, mentor AI engineers, and align technical strategies with healthcare business objectives while ensuring scalability, security, and operational excellence.