AI/ML Developer (ID 1442)

• 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 LangChain and LlamaIndex to develop LLM-powered applications and workflows.
  

• Work with basic AI agent frameworks such as LangGraph or CrewAI to build task-oriented AI solutions.
  

• Process and analyze structured and unstructured datasets using Pandas and NumPy.
  

• 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.
  

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 LangChain or LlamaIndex; exposure to LangGraph or CrewAI is an advantage.
  

• Basic experience with FastAPI or Flask and REST API development.
  

• Knowledge of SQL and data manipulation using Pandas and NumPy.
  

• 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.