Job description
Build and deploy intelligent applications using Machine Learning and Generative AI technologies. Work with Large Language Models (LLMs) such as: OpenAI Azure OpenAI Claude Gemini Design and develop Retrieval-Augmented Generation (RAG) systems. Develop scalable APIs using: FastAPI Flask Perform machine learning model training, inference, and evaluation.
Work on prompt engineering for optimizing LLM outputs. Build and manage AI pipelines using frameworks such as: Lang. Chain Llama. Index Lang. Graph CrewAI Handle structured and unstructured datasets using: Pandas Num. Py Work with embeddings and vector search implementations. Integrate vector databases such as: Pinecone FAISS Weaviate Chroma Collaborate with teams to integrate AI capabilities into real-world applications.
Use cloud and deployment tools for scalable AI solutions. Maintain code repositories and development workflows using Git and Jupyter Notebook.
Requirements
Strong programming skills in Python. Basic understanding of JavaScript / TypeScript (preferred). Experience in API development using FastAPI or Flask. Good understanding of: Machine Learning fundamentals Model training and inference Feature engineering Model evaluation metrics Hands-on experience working with LLM APIs such as: OpenAI Azure OpenAI Claude Gemini Knowledge of: Prompt Engineering Retrieval-Augmented Generation (RAG) Experience with AI/LLM frameworks: Lang.
Chain Llama. Index Lang. Graph CrewAI Strong data handling skills using Pandas and Num. Py. Understanding of embeddings and vector search concepts. Experience with SQL and vector databases. Basic knowledge of cloud platforms: AWS Azure GCP Familiarity with Docker, REST APIs, Git, and Jupyter Notebook. Passion for AI/ML and building scalable AI-powered applications.