Senior Data Scientist-Gen AI

Job description

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.