Job Description

Bangalore, Karnataka, India;Hyderabad, Telangana, India;Indore, Madhya Pradesh, India;Pune, Maharashtra, India;Noida, Uttar Pradesh, India




Qualification


:
Role: ML & GenAI Lead

Experience: 8-12+ years


Role Overview


The ML & GenAI Lead will be responsible for designing, leading, and delivering end-to-end Machine Learning and Generative AI solutions, with a strong focus on LLMs, Agentic AI frameworks, and production-grade ML systems. This role involves technical leadership, solution architecture, and close collaboration with business and engineering stakeholders.


Key Responsibilities


Lead the design and implementation of ML and GenAI solutions aligned with business use cases. Architect and deliver LLM-based systems, including RAG, prompt engineering, fine-tuning, and agentic workflows. Define and drive Agentic AI architectures using frameworks such as LangChain, LlamaIndex, CrewAI, AutoGen, or similar. Oversee model lifecycle management: data preparation, training, evaluation, deployment, and monitoring. Guide teams on MLOps / LLMOps best practices including CI/CD, model versioning, observability, and cost optimization. Collaborate with product, data, cloud, and platform teams to ensure scalable and secure AI solutions. Mentor and technically guide ML and GenAI developers. Ensure compliance with Responsible AI, security, and governance standards. Engage with stakeholders to translate business problems into AI-driven solutions.

Required Skills & Qualifications


Strong experience in Machine Learning, Deep Learning, and NLP. Hands-on expertise with LLMs (OpenAI, Azure OpenAI, Anthropic, Hugging Face, etc.). Proven experience building Agentic AI systems. Strong Python skills and ML frameworks: PyTorch, TensorFlow, Scikit-learn. Experience with RAG pipelines, vector databases (FAISS, Pinecone, Weaviate, Chroma). Solid understanding of cloud platforms (Azure / AWS / GCP) and containerization (Docker, Kubernetes). Experience with MLOps/LLMOps tools (MLflow, Kubeflow, Azure ML, LangSmith, etc.). Strong communication and leadership skills.

Experience


:
8 to 12 years


Job Reference Number


:
13505


Skills Required


:
Large Language Model, Agentic AI, Python, AWS, Machine Learning


Role


:
Role: ML & GenAI Lead

Experience: 8-12+ years


Role Overview


The ML & GenAI Lead will be responsible for designing, leading, and delivering end-to-end Machine Learning and Generative AI solutions, with a strong focus on LLMs, Agentic AI frameworks, and production-grade ML systems. This role involves technical leadership, solution architecture, and close collaboration with business and engineering stakeholders.


Key Responsibilities


Lead the design and implementation of ML and GenAI solutions aligned with business use cases. Architect and deliver LLM-based systems, including RAG, prompt engineering, fine-tuning, and agentic workflows. Define and drive Agentic AI architectures using frameworks such as LangChain, LlamaIndex, CrewAI, AutoGen, or similar. Oversee model lifecycle management: data preparation, training, evaluation, deployment, and monitoring. Guide teams on MLOps / LLMOps best practices including CI/CD, model versioning, observability, and cost optimization. Collaborate with product, data, cloud, and platform teams to ensure scalable and secure AI solutions. Mentor and technically guide ML and GenAI developers. Ensure compliance with Responsible AI, security, and governance standards. Engage with stakeholders to translate business problems into AI-driven solutions.

Required Skills & Qualifications


Strong experience in Machine Learning, Deep Learning, and NLP. Hands-on expertise with LLMs (OpenAI, Azure OpenAI, Anthropic, Hugging Face, etc.). Proven experience building Agentic AI systems. Strong Python skills and ML frameworks: PyTorch, TensorFlow, Scikit-learn. Experience with RAG pipelines, vector databases (FAISS, Pinecone, Weaviate, Chroma). Solid understanding of cloud platforms (Azure / AWS / GCP) and containerization (Docker, Kubernetes). Experience with MLOps/LLMOps tools (MLflow, Kubeflow, Azure ML, LangSmith, etc.). * Strong communication and leadership skills.