Senior Applied AI Engineer
$200,000–$250,000 year
On-siteSan Francisco, California, United States
San Francisco, California, United StatesOn-siteFull Time$200,000–$250,000 yearSenior LevelSmall
Full TimeSenior LevelSmall
Job Summary
Train and fine-tune open source models on proprietary datasets to push accuracy beyond off-the-shelf capabilities. Build eval pipelines, metrics, and feedback loops that measure model performance against real clinical outcomes. Design scalable, cost-efficient inference infrastructure with robust monitoring and observability. Develop agentic systems and interfaces that translate model capabilities into reliable clinician workflows. Prototype quickly, then harden systems for production use while staying current with frontier research and open source frameworks.
Required Qualifications
- 7+ years of professional software engineering experience
- Meaningful depth in AI/ML
- Experience training, fine-tuning, or evaluating LLMs and open source models
- Real opinions about what works and what does not
- Experience building agentic systems: tool use, generator and critic loops, planners and executors, and orchestration where one agent's output drives another's work
- Comfort building infrastructure that is fast, reliable, and cost-efficient at scale
- Startup experience shipping real features in high-growth environments
- A product mindset, comfort across the stack, and the ability to operate in ambiguity without a clean spec
- High standards for reliability and accuracy when real clinicians and patients depend on your work
Desired Qualifications
- Shipped real AI software to real users. You can describe something you built, what broke, and how you fixed it.
- Strong instincts for evals, observability, and the feedback loops that turn user feedback into measurable improvement
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