Top Machine Learning Jobs in India

Design, build, and deploy production-grade ML systems (NLP and Generative AI), own MLOps and observability, solve complex unstructured data problems, mentor engineers, and collaborate cross-functionally to deliver scalable, reliable ML solutions.

The role involves building scalable AI solutions, architecting software systems, and integrating machine learning technologies to improve healthcare services. Responsibilities include developing AI pipelines, optimizing models, and ensuring compliance with AI ethics.

Design, develop, and implement ML models for search and recommendation systems. Collaborate with data engineers and scientists to integrate, enhance and scale ML solutions for personalization in various sectors.

The ML Engineer will design, implement, and maintain backend services, integrate ML models, and collaborate with product owners and teams for efficient project execution.

The role involves designing, implementing, and maintaining backend services in Python for SMEs, integrating ML models, and collaborating with cross-functional teams.

Lead an AI/ML Research Engineering team to innovate observability solutions. Guide product development from research to deployment, focusing on AI techniques.

The Senior AI/ML Engineer will design and deploy generative AI solutions across cloud platforms, build scalable architectures, and collaborate with cross-functional teams to implement AI systems for optimization and compliance.

The Senior ML Engineer will own the ML lifecycle, develop production-grade systems, implement MLOps practices, and mentor junior engineers while collaborating with various stakeholders.

Design, build, and deploy GenAI-powered microservices and recommendation systems using LLMs, embeddings, and RAG. Build scalable Databricks/PySpark pipelines, implement vector retrieval with FAISS/ChromaDB/Pinecone, maintain ML APIs, and implement MLOps (model versioning, monitoring, retraining) and CI/CD for production ML infrastructure on AWS.

Lead the development and implementation of AI solutions, focusing on NLP and Generative AI, while mentoring a team of engineers and collaborating with cross-functional teams.

As a Machine Learning Engineer, you'll design, build, and deploy ML solutions across industries, owning the full ML lifecycle and creating impactful systems.

As a Data/ML Engineer, you will design and implement data pipelines, optimize workflows for unstructured data, and integrate LLM frameworks to power analytics and BI solutions.

Design, develop, and deploy production ML models; build feature pipelines; run experiments and A/B tests; monitor and maintain models; collaborate with engineers, product, and executives; mentor junior engineers and document models and processes.

Develop and deploy machine learning models, focusing on AI systems, while collaborating with product and engineering teams to integrate solutions.

Develop AI applications utilizing tools and cloud services, focusing on generative AI, deep learning, and neural networks while mentoring junior members and evaluating new technologies.

As an AI/ML Engineer, you will develop applications using AI tools and Cloud services, focusing on large language models, deep learning, and image processing. Responsibilities include leading team decisions and enhancing system performance through innovative AI techniques.

Develop applications utilizing AI tools and Cloud AI services, focusing on production-ready quality solutions, including deep learning and LLMs.

The AI/ML Engineer develops applications utilizing AI tools and cloud services, implements solutions using AI models, and collaborates with teams to enhance functionality.

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.

Design, implement, and improve end-to-end machine learning systems and GenAI applications. Build and deploy ML models and microservices in production, collaborate with product, design, and engineering to define strategy and deliver customer-facing features.