Top Machine Learning Jobs in India

Design, develop, and deploy AI/ML models (including NLP and LLM solutions) for Sales and Digital use cases; analyze data, build model APIs, collaborate cross-functionally, and translate AI research into production-ready capabilities while ensuring ethical, transparent model development.

Design, develop, and operationalize AI/ML, Generative AI, LLM, and agentic AI solutions. Build scalable batch, streaming, and cloud-native data pipelines using PySpark/Scala on Azure. Implement MLOps, CI/CD, model monitoring, RAG/vector search, and production-grade LLM applications. Collaborate with data science, architecture, and business teams, evaluate emerging AI tech, and produce prototypes, POCs, and documented deployments.

Build production-grade AI/ML systems, including LLM applications, agentic workflows, RAG pipelines, and scalable distributed ML models. Optimize model performance through prompt engineering, fine-tuning, evaluation, and observability. Collaborate with data scientists, software engineers, and product managers to deliver secure, reliable AI solutions at enterprise scale using Python, cloud services, and modern ML frameworks.

Design, productionize, and maintain scalable ML services and end-to-end pipelines. Build recommendation and classification models, optimize training/inference performance, develop reusable AI components, and collaborate with MLOps and platform teams to adopt best practices.

Build and maintain scalable data pipelines, feature stores, and ETL/ELT workflows to supply model-ready data for agentic AI and ML products. Implement data quality, validation, monitoring, privacy/residency controls, and structure data for RAG, feature engineering, and analytics while collaborating with AI engineers and contributing to design and code reviews.

Lead the Data and ML Platform team, defining vision and strategy, overseeing platform development, fostering innovation, and managing a distributed team.

The role involves maintaining and optimizing ML infrastructure, diagnosing complex issues, performing system optimization, and collaborating with engineers to resolve workflow issues.

The role involves designing and facilitating a Data+ML platform, building scalable ML pipelines, and collaborating with engineers to enhance data and ML capabilities.

Architects and deploys AI-powered applications and automated claims-testing solutions using Python, generative AI, agentic workflows, RAG, databases, cloud platforms, and DevOps tools. Develops test automation frameworks, data pipelines, microservices, and CI/CD processes; analyzes claims data for anomalies and reliability improvements. Collaborates with QA, business analysts, and cross-functional teams, provides technical leadership, mentors engineers, and supports responsible AI-assisted development.

Lead enterprise Generative AI and Agentic AI architecture, platform development, foundation-model selection and fine-tuning, RAG and vector retrieval, multi-agent workflows, AI observability, evaluation, governance, security, and cost optimization. Build scalable AI services across cloud providers, establish reusable frameworks and standards, and partner with engineering, product, security, architecture, and business leaders. Provide technical leadership and mentor AI practitioners while operationalizing reliable, compliant AI solutions.

Design and scale a unified AI/ML data collection platform supporting data pipelines, LLM and RAG workflows, model training, evaluation, deployment, observability, and lifecycle management. Build production-grade distributed and cloud-native systems, implement MLOps practices, monitor model performance and reliability, optimize costs, and mentor engineers while collaborating with product, research, engineering, and business teams.

Leads development of secure, scalable Java and Spring Boot microservices and APIs. Designs, tests, debugs, and operationalizes production software while improving engineering productivity through AI-assisted development tools. Builds AI agents and LLM-enabled workflows using Python, with appropriate grounding, validation, security, and guardrails. Supports Kubernetes operations, CI/CD, application resiliency, and responsible adoption of AI engineering practices across the team.

Designs, develops, integrates, and maintains automated systems and applications. Identifies automation opportunities, programs and configures technologies, develops performance and test scripts, leads CI/CD automation pipelines, executes testing, troubleshoots issues, documents processes, and optimizes performance against business KPIs. Provides technical direction and training to junior engineers while collaborating with internal stakeholders, external partners, and clients.

Leads Walmart Finance’s Reporting and Analytics Center of Excellence across Chennai and Bangalore. Defines multi-year reporting, analytics, AI, and transformation roadmaps; identifies finance AI/ML use cases; establishes governance, ethical AI, data quality, and operating frameworks; manages a 25+ person team and budget; drives Agile/DevOps adoption, executive communication, change management, and measurable ROI from reporting and AI initiatives.

Design, build, and evolve secure, scalable full-stack sales applications incorporating generative AI, intelligent workflows, APIs, data services, and cloud infrastructure. Lead architecture and technical design decisions, integrate AI models and retrieval systems, improve testing, CI/CD, observability, and production reliability, and mentor engineers. Collaborate with Product, AI/ML, Data, Security, Solution Architecture, and Engineering teams to deliver enterprise applications globally.

Leads enterprise automation strategy, architecture, development, deployment, governance, and support using UiPath and Microsoft Power Platform. Identifies automation opportunities, builds scalable integrations, applies AI, machine learning, document processing, conversational AI, and Celonis process mining, and manages automation lifecycle and platform improvements. Partners with global stakeholders, leads digital transformation programs, mentors engineers, and drives measurable operational efficiencies.

Leads solution architecture for frontier AI products, defining secure, scalable, and reusable architectures for AI applications and agentic workflows. Establishes engineering, platform integration, governance, observability, and production-readiness patterns; guides technical direction and architecture reviews; and advises cross-functional stakeholders on implementation tradeoffs, risks, delivery plans, and business outcomes.

Analyze large datasets, investigate data quality and lineage issues, document data sources and methodologies, build data pipelines, develop logical data models, and apply advanced analytics and AI/ML to identify trends. Create dashboards and automated reports, communicate complex findings, recommend operational improvements, and influence stakeholders. The role also involves managing risk and controls, supporting governance, and potentially leading or coaching analytical teams.

Deliver global people analytics projects end-to-end: gather requirements, extract and model HR data, build predictive ML/NLP solutions, define People KPIs, create visualizations, and present insights to HR and business leaders to improve workforce decision-making.

Develop and maintain scalable cloud-native SaaS software using Go and modern technologies. Responsibilities include hands-on coding, automated testing, cloud infrastructure, infrastructure as code, monitoring, troubleshooting, code reviews, technical design, mentoring, and cross-functional collaboration. The role requires experience with REST APIs, databases, containers, microservices, CI/CD, security practices, and Agile delivery, with opportunities to contribute to migrations and performance improvements.

Develop and maintain scalable cloud-native SaaS software using Go and modern technologies. Design architectures, build REST APIs and microservices, create automated API and UI tests, manage cloud infrastructure, and support CI/CD. Perform code reviews, troubleshooting, monitoring, root cause analysis, and security improvements while collaborating across global teams and mentoring junior engineers.

Design, build, and deploy production-ready AI/ML systems using cloud and on-prem pipelines. Apply generative AI, deep learning, chatbots, and image processing. Lead and mentor the team, drive cross-team decisions, and evaluate emerging AI technologies to enhance scalable solutions.

Leads the design, development, and maintenance of scalable search and backend systems. Deploys and manages machine learning models with data science teams, optimizes search algorithms and ML pipelines, integrates APIs and services, and contributes to architecture, code reviews, and engineering best practices. The role also includes technical leadership, mentoring, and collaboration across stakeholders.

Lead the design, development, deployment, and maintenance of scalable cloud-native platform capabilities for Walmart Connect’s sponsored search ad server. Build infrastructure, tooling, AI/ML frameworks, and distributed systems; conduct design reviews; drive software lifecycle activities; mentor engineers; influence architecture and technical decisions; and collaborate across teams to translate complex business needs into reliable, data-driven solutions.

Develop and deploy production-ready AI and machine learning applications using cloud AI services, generative AI, deep learning, neural networks, chatbots, and image processing. Responsibilities include translating stakeholder requirements into technical solutions, researching emerging AI technologies, preprocessing large datasets, testing and validating models, collaborating with teams, and mentoring junior colleagues.