Top Machine Learning Jobs in India

As an AI/ML Engineer, you will develop AI applications and systems, utilizing cloud services and models, ensuring quality and scalability. You will lead teams, provide solutions, and mentor within the team.

The AI / ML Engineer develops applications utilizing AI tools and cloud services, focusing on quality production solutions with generative AI and deep learning models.

The Senior Software Engineer will build and maintain ML Ops pipelines, deploy models, and enhance DevOps automation workflows.

The Cloud Developer III builds cloud applications, designs features, debugs code, and implements solutions, collaborating on various technical projects.

Optimize LLM performance and implement evaluation frameworks; build clustering models for customer and product segmentation; design and maintain data pipelines using SQL and Python DAGs.

Design, build, deploy, and maintain ML/DL and GenAI solutions (including RAG/agents) across the full lifecycle. Implement training/evaluation pipelines, automated retraining, monitoring/observability, multi-tenant guardrails, and production CI/CD integrations to scale reliable customer deployments.

The Technical Architect for AI/ML will define architecture for AI systems, mentor teams, and align strategies with business objectives, utilizing cloud-native tools and frameworks.

As a Senior AI Engineer, you will design and implement scalable AI systems, mentor junior engineers, and ensure impactful, ethical AI solutions. Responsibilities include collaborating with stakeholders and fine-tuning generative AI models.

Design, build, and deploy ML models for personalization and recommendations. Collaborate with teams, ensure performance, and mentor junior engineers.

Develop and deliver next-generation localization, mapping, perception, and autonomy capabilities for Spot. Research and integrate ML-based approaches, design experiments with simulated and real robot data, and produce performant C++ and Python code while shaping model, dataset, and pipeline strategy.

Build and maintain Python-based training and inference infrastructure, MLOps pipelines, data ingestion/versioning systems, and tools for performance optimization and on-robot/off-robot deployment. Drive CI/CD, testing, dashboards, and collaborate with central infrastructure to scale compute and reliability.

Seeking a Senior Machine Learning Engineer with expertise in multimodal generative AI, strong technical skills in AI models, and mentoring abilities.

Lead and grow an ML engineering team building content knowledge and discovery capabilities. Define ML roadmap, provide architecture and MLOps guidance, integrate generative AI and vision models, partner cross-functionally, and deliver scalable production ML solutions that improve search, recommendations, and ad experiences.

Design, build, and ship agent-driven chatbot and GenAI workflows; own features end-to-end from design to impact measurement; collaborate with product, ML, and engineering teams; use modern AI development tools and iterate to improve AI-assisted software.

The Senior Software Development Engineer L4 develops high-quality software by collaborating with teams, participating in design and code reviews, and ensuring compliance with security standards. Responsibilities include unit testing, debugging, and documentation, while promoting continuous improvement.

The Senior AI/ML Engineer will work on AI solutions, including Python development, Generative AI applications, and API integrations, while ensuring performance and scalability.

Lead development and deployment of advanced ML and generative AI solutions (LLMs and AI agents) to improve customer experience and personalization. Design, implement, and refine scalable, robust models, build evaluation frameworks for generative tasks, and collaborate cross-functionally to integrate ML into products and platforms.

As a Sr. ML Engineer, you'll design, build, and deploy ML solutions for various industries, leading the full ML lifecycle and collaborating with clients.

Design and implement AI and machine learning models, optimize systems, collaborate with teams, and analyze results to enhance performance.

Senior AI/ML (Data) Engineer responsible for statistical analysis, building and validating ML models, forecasting, and deploying models using MLOps tools. Works with probabilistic graphical models, monitoring frameworks, and modern ML frameworks to productionize and maintain agentic AI solutions.

Build and maintain ML models and services, ensuring performance, reliability, and compliance while collaborating with diverse teams to integrate and operationalize features.

Lead design and production of computer vision biometric systems (face detection, quality, attributes, recognition). Build/train models, implement fairness benchmarking, own end-to-end ML pipelines on AWS, optimize for low-latency inference, and mentor engineers.

The AI/ML Engineer will develop generative AI models, deploy ML models, write scalable code, and work with various AI technologies and frameworks.

Design, build, and productionize scalable AI/ML pipelines and models (including LLMs and Generative AI). Deploy and optimize models across cloud and edge, implement MLOps (CI/CD, versioning, monitoring), and collaborate with data scientists and engineering teams to deliver reliable, low-latency AI solutions.

Lead AI/ML projects, design scalable architectures, translate business needs into technical solutions, and ensure best practices in implementation.