Clinical Data Manager supporting research projects and managing patient databases at Mass General Brigham. Interact with patients and maintain data integrity in clinical research.
About the role
- Data Scientist developing and deploying Generative AI solutions including LLMs for various enterprise applications. Collaborating with teams to implement AI technologies effectively.
Responsibilities
- Lead the development and deployment of GenAI solutions, including LLM-based applications, prompt engineering, fine-tuning, embeddings, and retrieval-augmented generation (RAG) for enterprise use cases
- Design and build Generative AI solutions using Large Language Models (LLMs) for business problems across domains like customer service, document automation, summarization, and knowledge retrieval
- Fine-tune or adapt foundation models using domain-specific data
- Implement RAG pipelines, embedding models, vector databases (e.g., FAISS, Pinecone, ChromaDB)
- Collaborate with data engineers, MLOps, and product teams to build end-to-end AI applications and APIs
- Develop custom prompts and prompt chains using tools like LangChain, LlamaIndex, PromptFlow, or custom frameworks
- Evaluate model performance, mitigate bias, and optimize accuracy, latency, and cost
- Stay up to date with the latest trends in LLMs, transformers, and GenAI architecture
Requirements
- 6+ Years of experience in Data Science / ML
- 1+ year hands-on in LLMs / GenAI projects
- Strong Python programming skills, especially in libraries such as Transformers, LangChain, scikit-learn, PyTorch, or TensorFlow
- Experience with OpenAI (GPT-4), Claude, Mistral, LLaMA, or similar models
- Knowledge of vector search, embedding models (e.g., BERT, Sentence Transformers), and semantic search techniques
- Ability to build scalable AI workflows and deploy them via APIs or web apps (e.g., FastAPI, Streamlit, Flask)
- Familiarity with cloud platforms (AWS/GCP/Azure) and MLOps best practices
- Excellent communication skills with the ability to translate technical solutions into business impact
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