3 months ago
Base Salary
$225k - $300k/yr
Responsibilities
- Own end-to-end ML systems, including architecture, data, modeling, evaluation, and production infrastructure.
- Train and fine-tune large language models for clinical reasoning and medical question answering.
- Make and own tradeoffs across accuracy, latency, cost, and safety in production environments.
- Develop evaluation frameworks to ensure model safety and clinical validity.
- Integrate ML systems into product workflows and patient-facing applications.
- Monitor system performance in production and iterate based on real-world usage.
- Define what 'correct' means in ambiguous clinical workflows in collaboration with engineers and clinicians.
Requirements
- Strong foundation in machine learning and software engineering.
- Track record of building and owning ML systems in production.
- Experience driving ambiguous ML problems from 0→1.
- Hands-on experience with PyTorch or similar frameworks.
- Ability to operate independently in high-ambiguity environments.
- Strong product and engineering judgment.
- Comfort working in a fast-moving, early-stage environment.
- Experience working on systems with real-world consequences.
Benefits
- Work on high-stakes problems with real impact on patient care.
- Build systems that define how AI is trusted in clinical decision-making.
- Significant ownership in a small, high-caliber team.
- Competitive compensation and meaningful equity.