Key Responsibilities

Develop and deploy Generative AI and Machine Learning solutions
Build AI-powered applications, chatbots, copilots, and automation tools
Design and implement RAG pipelines, vector search, and prompt engineering techniques
Train, fine-tune, evaluate, and optimize ML/LLM models
Develop scalable APIs and integrate AI services with enterprise applications
Work with structured and unstructured datasets for model training and analytics
Collaborate with Data Engineers, DevOps teams, and business stakeholders
Monitor model performance, scalability, and reliability in production environments

Requirements

Strong experience in Python programming
Hands-on experience in Machine Learning and Deep Learning concepts
Experience with LLMs and Generative AI frameworks
Strong knowledge of Prompt Engineering and Retrieval-Augmented Generation (RAG)
Experience with LangChain, LlamaIndex, Hugging Face, or OpenAI APIs
Knowledge of Vector Databases such as Pinecone, FAISS, ChromaDB, or Weaviate
Experience in TensorFlow, PyTorch, or Scikit-learn
Knowledge of REST APIs, FastAPI, or Flask
Experience with cloud platforms such as AWS, Azure, or GCP
Familiarity with Docker, Kubernetes, and CI/CD pipelines
Good understanding of SQL/NoSQL databases