About Us: Savant is transforming how healthcare and life sciences organizations unlock the value trapped in unstructured medical data. Our platform combines cutting-edge large language models (LLMs) with domain-specific quality controls to convert free-text clinical records into structured, analysis-ready data — efficiently, accurately, and at scale. We work with leading institutions across healthcare, life sciences, and research, supporting faster studies, sharper insights, and better care.

Backed by Roivant (NASDAQ: ROIV), Savant is built for organizations that see structured data not just as an output, but as a foundation for innovation. The Opportunity: We’re hiring an AI/ML Engineer to help build and scale the infrastructure behind Savant’s clinical data structuring platform. In this role, you’ll work at the intersection of LLMs, applied machine learning, and healthcare data to develop production-grade pipelines that extract structured insights from messy, high-stakes records.

This is a high-impact engineering role with full-stack exposure - from prototyping model workflows to deploying scalable inference systems. You’ll work closely with our product, clinical, and engineering teams to continuously improve model performance and delivery quality. If you’re excited to build real-world applications of LLMs, shape how AI gets deployed in healthcare, and operate with ownership in a fast-paced startup environment, we’d love to hear from you.

What We'Re Looking For

: 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 Comfort working in fast-paced, ambiguous environments where iteration is key Clear communicator with a collaborative mindset Bonus Points For: Experience working with clinical or healthcare data (EMRs, registries, imaging, labs, etc.) Familiarity with model evaluation tooling, quality benchmarking, and drift detection Exposure to data privacy or compliance frameworks (HIPAA, de-ID workflows, etc.) Experience in an early-stage startup or small, fast-moving technical team

Why Join Us

Full-Stack AI Impact: Contribute across the ML lifecycle, from data to deployment Product-Embedded Work: Your contributions will ship as part of a real product, not just R&D Tight Collaboration: Work directly with cross-functional partners across clinical, product, and engineering Mission-Driven: Help unlock better healthcare by solving foundational data problems Base salary for this role will be determined during the interview process and will vary based on multiple factors, including but not limited to prior experience, relevant expertise, current business needs, and market conditions. The expected base salary for the role will generally be between $130,000 to $180,000 per year, with meaningful equity. The final salary offered may be outside this range based on individual circumstances and business and market conditions.

Compensation

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