Ai Ml Engineer

Role & responsibilities

• Design, develop, and implement AI/ML models using Python.
• Build Generative AI applications using LLMs and prompt engineering techniques.
• Develop RAG pipelines for document processing, semantic search, and knowledge retrieval.
• Implement NLP solutions such as text classification, entity extraction, summarization, and conversational AI.
• Work with frameworks such as LangChain, LangGraph, or LlamaIndex.
• Integrate vector databases and embedding models for semantic search and retrieval.
• Fine-tune, evaluate, and optimize ML models and LLM-based applications.
• Deploy and monitor AI solutions using APIs, cloud platforms, and MLOps practices.
• Collaborate with engineering and business teams to deliver reliable, scalable AI solutions.

Preferred candidate profile

• Strong programming experience in Python.
• Hands-on experience in Machine Learning and Deep Learning.
• Practical knowledge of NLP and Generative AI.
• Experience working with LLMs such as GPT, Llama, or similar models.
• Strong understanding of RAG architecture, embeddings, vector search, and retrieval pipelines.
• Experience with frameworks such as LangChain, LangGraph, or LlamaIndex.
• Familiarity with REST APIs, Git, and model deployment.

Perks and benefits