Top Machine Learning Jobs in India

The role involves leading complex engineering programs, managing project timelines, stakeholder communications, and driving product success through a collaborative approach.

Design, build, and launch efficient machine learning models while monitoring system health and performance, ensuring scalability, and collaborating with cross-functional teams.

Lead the design and deployment of AI-driven solutions and CI/CD pipelines, ensuring technical feasibility and compliance. Manage databases and optimize pipelines, guiding teams on AI/ML best practices.

The Senior Data Analyst will leverage data to inform strategic decisions, analyze complex datasets, develop predictive models, and communicate insights to stakeholders.

You will design and deploy AI solutions, enhance observability and automate insights. Responsibilities include building NLP models, AI-driven analytics, and collaborating with cross-functional teams.

Lead R&D and engineering of agentic AI systems and autonomous agents; design and prototype solutions, integrate LLMs and tools into scalable pipelines, publish research, mentor teams, collaborate with delivery and Responsible AI, and support client engagements with advanced AI expertise.

Develop AI applications and systems, focusing on agentic solutions and LLMs. Responsibilities include building pipelines, integrating databases, and deploying to cloud infrastructures.

Lead R&D in agentic AI, design and prototype autonomous agents, integrate LLMs and agentic workflows, collaborate across teams, publish research, mentor researchers/engineers, and support client engagements with advanced AI solutions.

Develop applications utilizing AI and Cloud services, create agentic systems, integrate vector databases, and ensure production readiness. Responsibilities also include prototyping AI solutions, optimizing systems, and managing cloud deployments.

Develop and deploy AI systems utilizing ML, GenAI models, and cloud services. Responsibilities include creating pipelines, integrating tools, and ensuring high-quality AI functionality.

As an AI/ML Engineer, you will design AI systems focusing on orchestration and model integration, ensuring scalability and security, while collaborating with cross-functional teams.

Develop AI systems leveraging LLMs and machine learning, focusing on autonomous agents and pipelines. Responsibilities include system architecture, model integration, and performance optimization.

The position involves developing AI systems, employing machine learning tools, creating autonomous agents, and integrating vector databases, with a focus on quality and performance.

Develop AI applications using GenAI models, build RAG pipelines, optimize AI systems, and integrate enterprise AI APIs. Requires hands-on experience with LLMs and strong Python skills.

Lead R&D and engineering of agentic AI systems, designing and prototyping autonomous agents, integrating LLMs and GenAI into scalable solutions, publishing research, mentoring teams, and supporting client engagements with advanced AI consulting.

The AI/ML Engineer will develop applications using AI tools and cloud services, focusing on system design and implementation, mainly using LLMs and agent frameworks.

Lead R&D and engineering of agentic AI and autonomous agents, design and prototype real-world solutions, integrate LLMs and GenAI into production systems, collaborate across teams, publish research, mentor researchers and engineers, and support complex client engagements with advanced AI expertise.

Lead R&D and design of agentic AI and autonomous agents; prototype and integrate agentic capabilities into scalable systems; collaborate with Responsible AI, delivery, and research partners; publish research; mentor researchers and engineers; support client engagements with advanced AI solutions.

Develop systems utilizing AI technologies, integrating LLMs and vector databases while building efficient pipelines and deploying AI solutions in production environments.

Lead R&D and engineering to design, prototype, and integrate agentic AI and autonomous agents using LLMs, reinforcement learning, and MLOps. Mentor teams, publish research, and support client solutioning and delivery across industries.

Develop AI applications and systems, focusing on agentic and LLM-powered solutions, building pipelines and integrating models into production. Requires hands-on experience with machine learning and AI tools.

Lead R&D and engineering to design, prototype, and deploy agentic AI and autonomous agents. Integrate LLMs and GenAI into scalable production systems, mentor teams, publish research, and support client solutioning with MLOps and cloud AI pipelines.

The role involves designing, building, and deploying AI systems, including agentic models and RAG pipelines, using various technologies and cloud platforms.

Develop applications utilizing AI and ML, focusing on system design and implementation, pipeline integration, and model deployment in a production environment.

Develop applications utilizing AI tools and Cloud AI services, focusing on creating agentic AI systems, RAG pipelines, and deploying AI models. Responsible for evaluating and integrating AI solutions into production environments.