AI/ML Lead - LLM Application

Responsibilities :

- Lead the architecture, design, and development of production-grade AI/ML solutions from POC - MVP - Production.

- Drive solutions across Machine Learning, Deep Learning, GenAI, LLMs, RAG, Agentic AI, NLP, Computer Vision, and MLOps.

- Design and implement advanced LLM/RAG pipelines, embeddings, vector search, evaluation, guardrails, and AI orchestration.

- Build single-agent and multi-agent AI workflows using frameworks such as LangGraph, LangChain, AutoGen, and CrewAI.

- Lead ML/DL development using Python, PyTorch, TensorFlow, Scikit-learn, and Hugging Face.

- Architect scalable AI infrastructure across AWS/Azure/GCP, with Docker, Kubernetes, GPU deployments, CI/CD, and MLOps.

- Lead and mentor AI/ML engineers, conduct design/code reviews, and drive technical decisions and engineering best practices.

- Collaborate with clients and stakeholders on technical consulting, solution architecture, POCs, proposals, estimates, and pre-sales.

Requirements:

- Strong hands-on expertise in Python, LLM application development, RAG, Agentic AI, FastAPI, REST APIs, PostgreSQL/MongoDB, cloud, Docker, and MLOps.

- Strong technical leadership, communication, problem-solving, mentoring, and international client-handling skills with experience delivering enterprise AI solutions.

Contact:

Jyoti Chawla,

Skills

Artificial Intelligence, Machine Learning, Generative AI, LLM, RAG, NLP, Computer Vision, Deep Learning, Agentic AI, Python, PyTorch