Top Machine Learning Jobs in India

Leads the architecture, development, and production delivery of AI/ML capabilities in enterprise healthcare applications. Builds ML and generative AI solutions, RAG systems, model-serving APIs, MLOps workflows, distributed cloud services, and CI/CD pipelines. Ensures responsible AI, security, privacy, reliability, monitoring, and operational readiness. Influences architecture across teams, mentors engineers, documents technical decisions, and delivers reusable production components.

Leads planning and execution of complex data science projects from business understanding through model deployment and monitoring. Coordinates product, engineering, data science, and leadership teams; manages roadmaps, dependencies, risks, trade-offs, escalations, and status reporting. Translates technical concepts into business language, drives continuous improvement, facilitates retrospectives, and ensures alignment across matrixed teams.

Designs and implements secure AI solutions and technical security controls; assesses AI systems for security and privacy risks; develops automation, monitoring, and detection capabilities; translates policies and regulations into controls; supports governance and audit readiness; and partners with engineering, security, risk, and business teams. The role also provides technical leadership and AI security education in an onsite, overnight-shift environment.

Owns product lifecycle management, market analysis, customer feedback, product roadmaps, NPI processes, launches, and revenue initiatives. Uses Generative AI, LLMs, predictive analytics, and AI agents to improve research, backlog prioritization, documentation, and competitive intelligence. Collaborates with technical and business stakeholders, mentors junior employees, supports distribution strategy, delivers product training, and oversees new product development. The role is remote within the United States and requires 8+ years of experience.

Leads strategy and execution for pricing, driver matching, and incentive products supporting delivery operations across international markets. Owns product vision, roadmaps, discovery, experimentation, analytics, launch execution, and value realization. Partners with Engineering, Design, Analytics, and business stakeholders to optimize driver experience, delivery performance, and cost per order. Influences technical direction, evaluates AI opportunities, mentors product managers, and addresses local regulatory and market requirements in Canada and Latin America.

Design, clean, analyze, and visualize data using SQL and Python; build Tableau dashboards; apply statistics and basic ML/DS concepts; follow software/data-engineering practices (version control, unit testing, high-performance code); work with structured and unstructured data and cloud environments.

Translates business needs into requirements, user stories, process flows, acceptance criteria, and measurable product outcomes for digital, analytics, automation, data science, and AI products. Leads discovery, stakeholder workshops, process and data analysis, testing, release readiness, governance, adoption tracking, and continuous improvement. Partners with business, product, engineering, data, quality, and technology teams while evaluating AI opportunities, responsible-use risks, data readiness, explainability, and business value.

Leads omnichannel customer engagement measurement and advanced analytics across CRM, media, field, and digital channels. Develops attribution, experimentation, incrementality, and causal inference frameworks; translates findings into optimization recommendations; mentors analysts; and builds scalable measurement capabilities. Partners with commercial, media, CRM, and activation teams to improve customer engagement effectiveness using Python or R, cloud analytics environments, machine learning, and analytical best practices.

Develop and support cloud-native, API-first internal product creation tools for Nike’s Consumer Product & Innovation teams. Collaborate with engineers, product managers, principal engineers, and cross-functional partners to build modular services and modern web applications. Responsibilities include applying software architecture patterns, developing with front-end frameworks, implementing AWS services, maintaining DevOps and CI/CD practices, using infrastructure as code, and applying modern testing methodologies. AI, machine learning, and data solution experience is preferred.

Leads IT systems analysis across Agile squads, directing requirements elicitation, backlog management, user story refinement, sprint reviews, release planning, and cross-functional collaboration. Partners with Product Owners, engineers, architects, and stakeholders to translate business needs into AI-enabled solutions while aligning with technical, security, governance, and process standards. Coordinates analysts, facilitates workshops, supports product vision and roadmap execution, and drives continuous improvement across the Agile delivery model.

Leads mainframe modernization and migration initiatives for large global clients. Develops transformation and re-platforming solutions, conducts discovery workshops, presents technical and business cases, advises executives, and partners with sales, consulting, operations, and product teams. Requires extensive mainframe expertise across legacy technologies, migration architecture, data modernization, cloud and hybrid environments, and enterprise hosting. The role also supports AI-driven modernization, technical documentation, project lifecycle management, and client relationship development.

Lead presales Solution Architect for UiPath Intelligent Automation. Run discovery workshops, design scalable enterprise automation, deliver demos/PoCs, produce technical proposals, define governance and integrations, and mentor teams while driving CoE and adoption.

Designs and implements cloud-native AI applications and data platforms on SAP BTP. The role develops LLM, RAG, and agentic capabilities; integrates machine learning services, data pipelines, REST/gRPC services, and vector databases; and ensures scalability, security, observability, and CI/CD. The engineer collaborates with customers, architects, product, UX, and data teams to identify problems, create AI-driven solutions, and deliver robust multi-tenant enterprise applications.

Lead enterprise detection engineering across SIEM, EDR, NDR, cloud, on-premises, and OT/ICS environments. Own detection strategy and content mapped to MITRE ATT&CK, optimize queries and reduce false positives, automate detection-as-code workflows, and partner with SOC, incident response, threat intelligence, and purple teams. Establish quality standards, validate coverage through adversary emulation, integrate threat intelligence, and lead platform and vendor collaboration.

Develop, design, test, maintain, and enhance scalable Java full-stack software solutions. Lead architecture and technical implementation, conduct code and architecture reviews, troubleshoot complex issues, improve code quality, and support customers. The role guides technical projects, mentors developers, evaluates technologies, and collaborates cross-functionally to deliver cloud-based SaaS products and modernization initiatives involving DevOps, AI, automation, and data platforms.

Develop and deploy production-grade AI systems and agentic workflows in enterprise environments. The role embeds with client teams to design architectures, integrate AI platforms with business systems, manage cloud-native deployments, and own outcomes from experimentation through production and handover. Responsibilities include AI governance, multi-provider platform integration, executive stakeholder engagement, client workshops, business-value measurement, and creation of reusable deployment patterns and accelerators.

Develop and maintain scalable Java full-stack software solutions, including technical design, implementation, testing, debugging, architecture reviews, and code reviews. Lead complex technical projects, improve existing systems, support customers, investigate technologies, and mentor developers. The role requires expertise in cloud infrastructure, DevOps, scalable web services, databases, software testing, security, AI modernization, LLMs, and cross-functional technical leadership.

Develop and maintain scalable Java full-stack software and distributed systems for large business environments. Responsibilities include technical design, coding, testing, debugging, architecture and code reviews, cloud and DevOps implementation, system modernization, documentation, and customer support. The role leads technical direction, mentors developers, evaluates emerging technologies, and collaborates with product, support, and cross-functional teams to deliver secure, high-performance solutions.

Develop and enhance scalable Java full-stack software, including highly available web services and distributed systems. Responsibilities include technical design, coding, testing, debugging, code reviews, architecture reviews, system improvements, and technical support. The role also involves cloud infrastructure, CI/CD, DevOps, database integration, security practices, mentoring developers, leading technical initiatives, and translating AI modernization opportunities into business impact.

Develop and enhance scalable Java full-stack software solutions for complex business environments. Responsibilities include technical design, coding, testing, maintenance, architecture and code reviews, debugging distributed systems, improving existing applications, and supporting customers. The role leads technical initiatives, mentors developers, evaluates new technologies, and collaborates with product, engineering, and cross-functional teams. Experience with cloud infrastructure, DevOps, web services, databases, testing practices, AI modernization, and enterprise systems is required.

Develop, maintain, test, and enhance scalable Java full-stack applications and distributed web services. Create technical designs, lead architecture and code reviews, troubleshoot complex systems, and support cloud-based SaaS infrastructure. Collaborate across teams, improve code quality and operational processes, investigate emerging technologies, and mentor developers. The role emphasizes AWS or Azure, DevOps, CI/CD, big data, AI modernization, security, testing, and high-performance systems.

Develop, enhance, test, and support scalable Java full-stack applications and distributed systems. Create technical designs, lead architecture and code reviews, improve existing codebases, and troubleshoot complex issues. Work with cloud infrastructure, DevOps, databases, big data, security, testing, and AI modernization initiatives. Collaborate with cross-functional teams, provide technical guidance, and mentor developers while driving high-quality delivery and independent decision-making.

Develop and enhance scalable Java full-stack software solutions, including web services and distributed systems. Responsibilities include technical design, coding, testing, debugging, code reviews, architecture reviews, documentation, system quality improvements, and technical support. The role leads architecture and implementation efforts, mentors developers, collaborates cross-functionally, and works with cloud infrastructure, CI/CD, big data, AI modernization, and security practices.

Leads the design and production deployment of advanced machine learning solutions across NLP, machine perception, and Generative AI. Establishes technical vision, develops and optimizes neural network architectures, automates ML workflows, architects data pipelines, and drives scalable model integration, lifecycle management, and continuous improvement. Mentors engineers and balances model quality, reliability, latency, scalability, and cost in production environments.

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.