▸ 3–5 years of professional experience in AI/ML engineering, applied research, or related software roles.

▸ Robust proficiency in Python for building production-grade AI/ML systems and microservices.

▸ Demonstrated experience building and fine-tuning ML models using TensorFlow, PyTorch, or scikit-learn for production-scale deployments.

▸ Hands-on experience with Model Context Protocol (MCP) — building MCP servers and clients, and integrating them within agentic or LLM-powered systems for standardised tool and data-source connectivity.

▸ Practical exposure to LLM frameworks and integration: LangChain or LlamaIndex for orchestration and RAG pipelines, and direct API integration with OpenAI or Anthropic (prompt engineering, tool use, embeddings).

▸ Experience with vector databases — Pinecone, Weaviate, Qdrant, or pgvector — for semantic search and RAG workflows.

▸ MLOps proficiency: experiment tracking (MLflow, Weights & Biases), CI/CD for ML, model registries, and feature stores.

▸ Solid grounding in statistics,



linear algebra, and optimisation fundamentals essential for ML model development and evaluation.

▸ Experience designing autonomous AI agents and multi-agent workflows using LangGraph, AutoGen, or CrewAI with tool-use and function-calling patterns.

▸ Experience with Docker and Kubernetes for containerisation, orchestration, and scalable AI/ML system deployment.

▸ Proficiency in CI/CD pipeline design for AI/ML systems, including automated testing, model validation, and deployment tooling.

▸ Deep understanding of microservices design patterns, distributed systems, and RESTful API design for building scalable AI/ML infrastructure.

▸ Deep understanding of microservices design patterns, distributed systems, and RESTful API design for building scalable AI/ML infrastructure.

Pay: ₹1,200,000.00 per month

Work Location: In person

📌 AI/ML Engineer (India)
🏢 Nimap Infotech
📍 India