AI Engineer

AI Engineer (LLM, Machine Learning Data Engineering)

Job Summary

We are looking for a AI Engineer with strong expertise in Large Language Models (LLMs), Machine Learning, and Agentic AI to build intelligent, AI-driven enterprise solutions. The ideal candidate should have hands-on experience in customizing and fine-tuning transformer models, training machine learning models, implementing RAG pipelines, and integrating AI services into scalable applications.

Location: Kochi

Experience: 4-8 Years

Job Type: Full Time

Responsibilities

• Design, develop, and deploy AI-powered applications using LLMs and Agentic AI frameworks.
• Customize, fine-tune, and optimize pre-trained transformer models for domain-specific use cases.
• Build, train, evaluate, and optimize Machine Learning models.
• Develop Retrieval-Augmented Generation (RAG) pipelines and AI agents.
• Perform data cleaning, preprocessing, feature engineering, and model evaluation.
• Implement model re-ranking techniques to improve AI response quality and relevance.
• Integrate AI models with enterprise applications through APIs.
• Collaborate with cross-functional teams to deliver scalable, production-ready AI solutions.

Required Skills

• Strong proficiency in Python and FastAPI.
• Hands-on experience with Transformer models (Hugging Face, BERT, Llama, etc.).
• Experience in customizing and fine-tuning pre-trained models.
• Experience with model training, evaluation, and model re-ranking.
• Strong understanding of LLMs, RAG, Prompt Engineering, and Agentic AI frameworks (LangChain, LangGraph, CrewAI, AutoGen, etc.).
• Experience with PyTorch, TensorFlow, or Scikit-learn.
• Knowledge of Vector Databases (Pinecone, Qdrant, Chroma, Weaviate).
• Experience with REST APIs, Azure, or AWS.
• Strong analytical, problem-solving, and communication skills

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.