Data Scientist -2 (LLM/GenAI)

Job Description

We are looking for a highly skilled Data Scientist (LLM) to join our AI and Machine Learning team. The ideal candidate will have a strong foundation in Machine Learning (ML), Deep Learning (DL), and Large Language Models (LLMs) , along with hands-on experience in building and deploying conversational AI/chatbots . The role requires expertise in LLM agent development frameworks such as LangChain, LlamaIndex, AutoGen, and LangGraph . You will work closely with cross-functional teams to drive the development and enhancement of AI-powered applications. Key Responsibilities: Develop, fine-tune, and deploy Large Language Models (LLMs) for various applications, including chatbots, virtual assistants, and enterprise AI solutions. Build and optimize conversational AI solutions with at least 1 year of experience in chatbot development. Implement and experiment with LLM agent development frameworks such as LangChain, LlamaIndex, AutoGen, and LangGraph . Design and develop ML/DL-based models to enhance natural language understanding capabilities. Work on retrieval-augmented generation (RAG) and vector databases (e.g., FAISS, Pinecone, Weaviate, ChromaDB) to enhance LLM-based applications. Optimize and fine-tune transformer-based models such as GPT, LLaMA, Falcon, Mistral, Claude, etc. for domain-specific tasks. Develop and implement prompt engineering techniques and fine-tuning strategies to improve LLM performance. Work on AI agents, multi-agent systems, and tool-use optimization for real-world business applications. Develop APIs and pipelines to integrate LLMs into enterprise applications. Research and stay up to date with the latest advancements in LLM architectures, frameworks, and AI trends . Requirements Required Skills Qualifications: 3-5 years of experience in Machine Learning (ML), Deep Learning (DL), and NLP-based model development. Hands-on experience in developing and deploying conversational AI/chatbots is Plus Strong proficiency in Python and experience with ML/DL frameworks such as TensorFlow, PyTorch, Hugging Face Transformers . Experience with LLM agent development frameworks like LangChain, LlamaIndex, AutoGen, LangGraph . Knowledge of vector databases (e.g., FAISS, Pinecone, Weaviate, ChromaDB) and embedding models . Understanding of Prompt Engineering and Fine-tuning LLMs . Familiarity with cloud services (AWS, GCP, Azure) for deploying LLMs at scale. Experience in working with APIs, Docker, FastAPI for model deployment. Strong analytical and problem-solving skills. Ability to work independently and collaboratively in a fast-paced environment. Good to Have: Experience with Multi-modal AI models (text-to-image, text-to-video, speech synthesis, etc.) . Knowledge of Knowledge Graphs and Symbolic AI . Understanding of MLOps and LLMOps for deploying scalable AI solutions. Experience in automated evaluation of LLMs and bias mitigation techniques . Research experience or published work in