Job Description

Job Overview :- We are looking for a Machine Learning Engineer / Data Scientist with a strong background in Machine Learning (ML), Natural Language Processing (NLP), and Large Language Models (LLMs) . The ideal candidate has 4+ years of ML/NLP experience and at least 1 year of hands-on experience with LLMs , including fine-tuning, retrieval-augmented generation (RAG), and AI-driven agents . You will work on developing and fine-tuning transformer-based models, building AI-powered agents, and implementing generative AI solutions for real-world applications . If youre excited about LLM advancements and AI-driven automation , this role is for you. Key Responsibilities Fine-tune and optimize LLMs (GPT, LLaMA, Mistral, Falcon, T5, etc.) for domain-specific applications. Develop and integrate AI agents using CrewAI, LangChain, AutoGPT, and OpenAI function calling . Build and enhance retrieval-augmented generation (RAG) pipelines with FAISS, Pinecone, ChromaDB, and Weaviate . Design NLP models for text classification, summarization, NER, question answering, and conversational AI . Optimize embedding-based search, semantic retrieval, and transformer-based models for AI-driven workflows. Evaluate model performance, mitigate bias, and improve model interpretability using responsible AI techniques . Stay updated with the latest LLM advancements and contribute to open-source AI research and applications . Required Qualifications Skills Machine Learning NLP: 4+ years in ML/NLP/Deep Learning, with at least 1+ year working on LLMs. Programming: Python (PyTorch, TensorFlow, JAX). LLM Fine-Tuning: LoRA, QLoRA, PEFT, Instruction Tuning. AI Agents Orchestration: CrewAI, LangChain, AutoGPT. Retrieval-Augmented Generation (RAG): FAISS, ChromaDB, Pinecone, Weaviate. Deep Learning Frameworks: Hugging Face Transformers, OpenAI APIs, LLaMA models. Good-to-Have: Experience with multi-modal AI (text-to-image, speech-to-text, etc.) . Knowledge of contrastive learning, RLHF (Reinforcement Learning with Human Feedback) . Contributions to open-source AI projects or research papers . Experience Education Requirements 4+ years of experience in ML/NLP , with 1+ year working on LLMs . Bachelor s/Master s degree in Computer Science, AI, Machine Learning, or a related field. Publications or open-source contributions in AI/ML are a plus .