Senior/Lead Data Scientist

Job description

Senior Data Scientist - Generative AI We are looking for a Senior Data Scientist with hands-on experience in Generative AI (GenAI) to drive innovation through cutting-edge AI/ML solutions. This role involves designing and implementing GenAI models and pipelines that solve business problems and enhance productivity. You will collaborate with cross-functional teams to deliver solutions using large language models (LLMs), transformers, and other generative techniques. \\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\ Key Responsibilities: • Develop and fine-tune Generative AI models using LLMs (e.g., GPT, LLaMA, Claude, PaLM) for tasks like summarization, content generation, question answering, semantic search, etc. • Build end-to-end GenAI-powered solutions including prompt engineering, model training/fine-tuning, evaluation, and deployment. • Use frameworks like LangChain, LlamaIndex, and vector databases (e.g., FAISS, Pinecone, Weaviate) to build RAG (Retrieval-Augmented Generation) pipelines. • Collaborate with product, engineering, and business stakeholders to identify AI opportunities and prototype solutions. • Conduct experiments, evaluate model performance, and optimize for accuracy, latency, and relevance. • Contribute to the development of GenAI best practices and reusable assets within the organization. • Stay up to date with the latest research and developments in the GenAI and LLM space. \\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\ Required Skills and Experience: • 5+ years of experience in Data Science or AI roles, with 2+ years in GenAI or LLMs. • Strong Python skills and experience with transformers, Hugging Face, PyTorch, or TensorFlow. • Deep understanding of NLP, language modeling, and generative techniques. • Experience with prompt engineering, fine-tuning or few-shot learning. • Hands-on experience with LangChain, LlamaIndex, or similar GenAI orchestration frameworks. • Working knowledge of vector stores, embedding models, and retrieval techniques. • Experience with model deployment in cloud or hybrid environments (e.g., Azure, AWS, GCP). • Familiarity with MLOps tools and best practices is a plus. \\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\ Preferred Qualifications: • Masters or PhD in Computer Science, Machine Learning, Artificial Intelligence, or a related field. • Experience with OpenAI, Anthropic, Meta AI, or Google Cloud GenAI APIs. • Background in chatbot development, co-pilot solutions, or enterprise GenAI applications. • Publications or contributions to open-source projects in the GenAI space are a plus.