AI/ML Developer

Develop, test, and deploy AI/ML applications using Python and modern Generative AI technologies. Work with Large Language Models (LLMs) such as OpenAI, Azure OpenAI, Claude, and Gemini to build intelligent applications. Develop and implement Retrieval-Augmented Generation (RAG) pipelines to retrieve relevant information and generate context-aware responses.

Design and optimize prompts to improve the accuracy, relevance, and reliability of LLM outputs. Build and integrate REST APIs using FastAPI or Flask to connect AI/ML models with applications. Apply fundamental machine learning techniques, including model training, inference, feature engineering, and model evaluation. Use frameworks such as Lang.

Chain and Llama. Index to develop LLM-powered applications and workflows. Work with basic AI agent frameworks such as Lang. Graph or CrewAI to build task-oriented AI solutions. Process and analyze structured and unstructured datasets using Pandas and Num. Py. Implement embeddings and vector search to support semantic search and RAG applications.

Work with SQL and vector databases such as FAISS, Pinecone, Weaviate, or Chroma. Assist with deploying AI applications using cloud platforms such as AWS, Azure, or GCP, and containerization tools such as Docker. Use Git, Jupyter Notebook, and other development tools to maintain code quality, collaborate with team members, and document solutions.

Troubleshoot, test, and optimize AI/ML applications for performance, accuracy, and scalability.

Requirements

B.E./B.Tech in Computer Science, Information Technology, Artificial Intelligence, Data Science, or a related engineering discipline from a Tier 1 or Tier 2 college/university. 0–3 years of experience in AI/ML development, Generative AI, or software development, including relevant internships and projects. Strong programming skills in Python and a good understanding of data structures, algorithms, and object-oriented programming.

Basic understanding of machine learning concepts, model training, inference, feature engineering, and evaluation metrics. Familiarity with LLM APIs, prompt engineering, and Generative AI application development. Understanding of RAG architecture, embeddings, semantic search, and vector databases. Familiarity with AI development frameworks such as Lang.

Chain or Llama. Index; exposure to Lang. Graph or CrewAI is an advantage. Basic experience with FastAPI or Flask and REST API development. Knowledge of SQL and data manipulation using Pandas and Num. Py. Basic understanding of cloud platforms such as AWS, Azure, or GCP, along with Docker and Git. Strong analytical, problem-solving, debugging, and communication skills.

Ability to learn new technologies quickly and collaborate effectively in a team environment. Academic projects, personal projects, internships, or GitHub contributions demonstrating practical AI/ML or Generative AI skills are an advantage.