- 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.