Top Machine Learning Jobs in India

Manage the enterprise governance, risk, and compliance program across HIPAA, HITRUST, SOC 2, PCI DSS, vendor risk, audits, and healthcare data protection. Lead risk assessments, control documentation, remediation, client assurance, third-party reviews, and executive reporting. Develop responsible AI governance for healthcare revenue cycle management, including privacy, security, bias, transparency, and regulatory risk controls. Coordinate cross-functional compliance initiatives and support incident response, business continuity, and employee awareness programs.

Designs, develops, tests, deploys, and supports UiPath automation solutions, including attended and unattended bots, Orchestrator workflows, and REFramework implementations. Identifies hyperautomation opportunities and builds intelligent document processing, AI-assisted workflows, RAG solutions, chatbots, AI agents, and predictive or classification models. Integrates enterprise applications through APIs, mentors developers, performs code reviews, resolves production issues, and collaborates with business stakeholders on AI use cases.

Own the strategy, roadmap, growth, and lifecycle delivery of an Exposure Management application. Translate cybersecurity, vulnerability, identity, attack-path, and control data into actionable product capabilities using AI and knowledge graphs. Partner with clients, Sales, Marketing, Engineering, and Client Solutions to prioritize features, support go-to-market activities, and drive cross-sell. Lead and develop Product Owners while advancing agile, client-focused product practices.

Drive full-cycle sales for complex, high-value AI research workspace opportunities. Originate and close new business, support strategic renewals, expand stakeholder relationships, lead value-based workshops, and translate AI and research analytics capabilities into measurable customer outcomes. Engage senior decision-makers across enterprise, government, academic, and research organizations while developing pipelines, territories, business cases, negotiations, and long-term account growth.

Owns the full sales cycle for complex, high-value AI research workspace opportunities, from prospecting and discovery through negotiation and closure. Builds executive stakeholder relationships, generates new business, supports strategic renewals, leads workshops, develops business cases, and communicates measurable value from AI-powered research and knowledge workflow solutions. Requires enterprise sales expertise, AI fluency, consultative selling skills, and extensive regional travel.

Lead the design, development, and operation of enterprise Agentic AI and ML platforms. Build agent orchestration workflows, APIs, custom connectors, integrations, monitoring, observability, and reliable cloud-based systems. Establish LLMOps, MLOps, governance, security, and lifecycle-management practices; troubleshoot complex platform issues; lead technical prototypes; document architectures; and mentor engineers. The role focuses on scalable Agentic AI solutions using cloud, orchestration, and modern ML tooling.

Provide advanced analytics and AI/ML support for life sciences clients, particularly pharmaceutical commercialization initiatives. Lead India-based delivery teams, manage complex analytical projects, develop client recommendations, enhance consulting services, and support business development. The role requires hands-on work with Python, visualization tools, cloud platforms, and pharmaceutical use cases, along with mentoring, stakeholder collaboration, and communication with US clients.

Build and maintain scalable MLOps infrastructure, pipelines, GPU clusters, deployment automation, observability, and model lifecycle tooling for robotics products and research. Responsibilities include transforming prototypes into production solutions, optimizing training and evaluation pipelines, managing CI/CD and data workflows, monitoring platform health, collaborating cross-functionally, and mentoring contributors.

Conduct applied AI research in computer vision and machine learning for public safety and video security. Develop, prototype, optimize, and deploy models for edge and cloud environments, including vision-language and Transformer-based systems. Review research, create patents, collaborate with software teams, improve ML deployment processes, and establish rigorous performance evaluation frameworks. The role requires production-quality coding, dataset collaboration, and model optimization for latency, throughput, and computational efficiency.

Design, develop, and deploy production-grade Generative AI and Agentic AI applications. Build autonomous agents, multi-agent workflows, tool-calling systems, and enterprise AI integrations using LLMs, APIs, knowledge sources, RAG, and vector databases. Create scalable architectures, evaluate and improve model performance, and collaborate with product, engineering, and business teams to deliver secure, reliable AI solutions.

Develop artist-facing and backend tools that extend SideFX Houdini and integrate with VFX and CG production pipelines. Build clean, testable, maintainable software using HOM, HDK, Python, and/or C++. Collaborate with artists, developers, and project managers across the software lifecycle, while emphasizing usability, documentation, UX, reliability, and adoption. Support procedural workflows, production tools, simulations, rendering, and distributed studio systems.

Build Python-based tools for layout, animation, matchmove, and previs artists working with complex CG scenes. Develop scene-management systems, asset and animation library integrations, and 3DEqualizer data import/export workflows. Collaborate with product owners and stakeholders in an Agile environment, contributing across design, development, maintenance, and pipeline integration. Work may include front-end and back-end development for high-end VFX and feature animation pipelines.

Develop artist-facing and backend tools that extend Autodesk Maya and integrate with VFX and CG pipelines. Build reliable, maintainable software using HOM, HDK, Python, C++, MEL, and Maya APIs; improve workflows, usability, and adoption; and collaborate with artists, developers, and project managers throughout the software lifecycle. The role also involves documentation, testing, deployment, support, roadmap planning, and innovation across distributed VFX production teams.

Leads strategy, roadmap, and end-to-end development of ML-powered generative AI products. Defines requirements, prioritizes backlogs, integrates ML models into scalable experiences, tracks product metrics, evaluates emerging technologies, and coordinates cross-functional teams spanning ML research, engineering, data, UX, and creative functions.

Lead a team building user-facing product features that leverage the ML platform. Design scalable, reliable frameworks and APIs, develop full-stack features, resolve production issues, ensure performance and security, and collaborate across teams while participating in code and design reviews.

Develops enterprise data science and machine learning solutions across forecasting, classification, optimization, ecommerce, and market mix modeling. Responsibilities include sourcing and engineering data, building scalable models, communicating insights, collaborating with technical teams, creating automation solutions, and establishing data science standards and processes. The role also supports innovation involving generative and agentic solutions.

Lead enterprise data science solutions spanning machine learning, deep learning, Generative AI, Agentic AI, NLP, and RAG. Frame business problems, develop and evaluate models, design production AI workflows, and collaborate on deployment, monitoring, MLOps, governance, and Responsible AI. Provide technical leadership, mentor junior team members, manage stakeholder relationships, and establish data science best practices across the organization.

Develop scalable AI and machine learning solutions for forecasting, optimization, classification, ecommerce, and operational analytics. Partner with stakeholders and engineering teams to deploy, monitor, and improve models. Apply supervised and unsupervised learning, NLP, time series, and mathematical optimization techniques. Contribute to data science standards, documentation, knowledge sharing, and community practices while translating business needs into measurable outcomes.

Leads AI and data science strategy, model development, technical exploration, deployment, and post-production performance management. Manages and mentors a team of data scientists, prioritizes projects and resources, partners with stakeholders, and promotes AI literacy. The role requires expertise in machine learning, MLOps, Vertex AI, generative and agentic AI, stakeholder engagement, and people leadership.

Designs, develops, and operates enterprise automation and AI-enabled solutions using ServiceNow, Power Platform, machine learning, and agentic AI. Builds workflows, portals, applications, integrations, and CSM solutions; supports platform modernization, governance, security, testing, and production stability. Provides technical leadership, troubleshooting, vendor coordination, stakeholder collaboration, and team coaching while driving adoption of emerging automation technologies.

Lead the end-to-end technical product lifecycle for an AI-powered commercial lending suite. Define requirements, workflows, AI behavior, data models, APIs, integrations, evaluation standards, release readiness, monitoring, and deployment playbooks. Partner with Engineering, AI/ML, UX, Customer Success, and enterprise stakeholders to deliver reliable, explainable, reusable products for regulated environments while balancing customer needs with platform scalability.

Develop advanced analytics, AI/ML models, data pipelines, dashboards, and reporting solutions for Identity and Access Management controls. Analyze identity and entitlement data to detect anomalies, toxic access, control gaps, and IAM risks. The role also embeds model governance, AI risk management, explainability, monitoring, audit traceability, and responsible AI practices while partnering with security, risk, audit, compliance, privacy, and technology stakeholders.

Analyzes credit, bureau, transactional, and repayment data to identify risk drivers and improve lending decisions. Builds credit risk features and predictive model inputs, supports policy experimentation, monitors model and feature performance, and conducts portfolio analytics such as vintage, roll-rate, collections, and loss-driver analysis. Collaborates with engineering and data teams on quality, lineage, reproducible pipelines, governance, and production-ready documentation.

Design, build, and scale enterprise AI-powered platforms using GenAI, LLMs, RAG, embeddings, and NLP pipelines. Architect distributed, microservices-based, event-driven systems and production-grade APIs using Go or Python, cloud platforms, databases, and containerized deployments. Lead system design, secure engineering, CI/CD, observability, reliability, and troubleshooting. Influence technical direction across teams, mentor engineers, collaborate with stakeholders, and drive end-to-end delivery of scalable AI solutions.

Designs and delivers enterprise AI and machine learning solutions, including generative AI, fine-tuned LLMs, RAG, agentic systems, Document AI, OCR, and model deployment. Partners directly with business stakeholders to gather requirements, architect solutions, and own end-to-end delivery. Applies supervised, unsupervised, reinforcement learning, deep learning, and NLP techniques using Python, PyTorch, cloud platforms, APIs, and containerized environments. Healthcare experience is preferred.