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Savant is looking to solve the problem of unlocking the value trapped in unstructured medical data for healthcare and life sciences organizations

Requirements

• 3+ years of hands-on experience building and deploying ML/AI systems
• Strong Python development skills, including experience with production-quality ML codebases
• Familiarity with modern ML/NLP frameworks (e.g., PyTorch, Hugging Face, spaCy)
• Experience working with large-scale unstructured or semi-structured data
• Practical knowledge of LLMs: prompt engineering, evaluation, fine-tuning, observability
• Experience working with clinical or healthcare data (EMRs, registries, imaging, labs, etc.)
• Familiarity with model evaluation tooling, quality benchmarking, and drift detection

Responsibilities

• Design and build robust ML pipelines to apply LLMs and other models to unstructured clinical text
• Develop and optimize systems for information extraction, entity resolution, data normalization, and QA
• Build and scale infrastructure for running model inference across large datasets
• Prototype, evaluate, and refine prompt strategies, model configurations, and workflows
• Implement internal tools for monitoring, observability, and iterative model improvement
• Translate research prototypes into reliable, testable, and maintainable production code
• Collaborate cross-functionally with clinical experts and product leads to embed domain knowledge into model workflows

Other

• 3+ years of experience
• Clear communicator with a collaborative mindset
• Comfort working in fast-paced, ambiguous environments where iteration is key
• Base salary for this role will be determined during the interview process
• This position is at-will and Savant reserves the right to modify base salary at any time