Senior Data Scientist
Role summary
A leading integrated healthcare innovator is seeking a Senior ML/GenAI Engineer to bridge research and production systems. This role involves architecting MLOps pipelines and deploying LLM solutions using Python, PyTorch, and LangChain. Responsibilities include designing GenAI solutions, optimizing MLOps infrastructure on cloud platforms (Azure/AWS) with Kubernetes and CI/CD, developing AI tools for healthcare workflows, and building RAG pipelines. Collaboration with data engineering teams to integrate AI into EHR platforms like EPIC is key. The position requires 5+ years of experience in production ML systems, with at least 1 year in LLMs, and mastery of Python, deep learning stacks, and orchestration tools.
We're working with a leading integrated healthcare innovator transforming patient outcomes through large-scale AI on this exciting opportunity.
As a Senior ML/GenAI Engineer, you will bridge the gap between experimental research and production-grade systems, architecting robust MLOps pipelines and deploying cutting-edge LLM solutions. You will be at the forefront of the AI shift in healthcare, leveraging Python, PyTorch, and LangChain to build everything from clinical copilots to advanced RAG-based knowledge systems.
The Role
- Lead the end-to-end design and deployment of scalable GenAI solutions, from initial prototyping and prompt engineering to production monitoring and guardrail implementation.
- Architect and optimize MLOps infrastructure using Kubernetes, CI/CD, and ML platforms (Azure/AWS) to ensure seamless model orchestration and high-availability systems.
- Develop internal and client-facing AI toolsets including search-knowledge assistants, summarization tools, and conversational analytics to automate healthcare workflows.
- Build and refine RAG (Retrieval-Augmented Generation) pipelines, managing embedding strategies and high-performance Vector Databases (e.g., LlamaIndex).
- Collaborating with cross-functional software and data engineering teams to integrate AI models directly into EHR platforms like EPIC.
What You'll Need
- 5+ years of experience building production-grade software/ML systems, with a minimum of 1 year dedicated to LLMs and Generative AI.
- Mastery of Python and deep learning stacks (PyTorch, Transformers) alongside experience with LangChain, orchestration tools (MLFlow, Kubeflow), and Vector DBs.
- Proven track record of delivering production RAG systems, including expertise in prompt engineering, evaluation frameworks (guardrails), and latency optimization.
- Strong background in Big Data and SQL environments (Postgres, Redshift, Snowflake) and distributed systems architecture.
- Specific experience with healthcare datasets (EHR/EPIC) or highly regulated environments is strongly preferred.
What's On Offer
- Competitive compensation range of $91,416 - $152,380 based on impact and experience.
- Fully remote flexibility across 29 eligible states with a focus on work-life harmony.
- Comprehensive benefits including $10k Student Debt Pay Down, $10k Adoption/Fertility reimbursement, and $5,250 annual tuition assistance.
- Strong career growth paths with funding for professional certifications and continuing education.
Apply via Haystack today!
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