Latent Health
Machine Learning Engineer
$225K–$300K
San Francisco · On-site · Full-time · Posted Sep 29, 2026
About the job
Own and operate production-grade machine learning systems for clinical workflows, from problem definition and model development through deployment and monitoring.
What you'll do
- Design, build, evaluate, and operate end-to-end ML systems, including data and production infrastructure.
- Train and fine-tune LLMs for clinical reasoning, medical question answering, and evidence-grounded generation; integrate them into product workflows.
- Develop safety and clinical-validity evaluations, make production tradeoffs, and improve systems using real-world feedback.
What they ask for
- Strong foundation in machine learning and software engineering.
- Track record of building and owning production ML systems where performance, reliability, or correctness materially mattered.
- Experience taking ambiguous ML problems from 0→1, including problem formulation, model design, and productionization.
- Hands-on experience with PyTorch or similar frameworks.
Nice to have
- Experience deploying LLMs in production environments.
- Experience with distributed systems, large-scale data pipelines, or clinical, biomedical, or other regulated datasets.
Pay
$225K – $300K (base salary)
Tools
PyTorch
AI focus
Train and fine-tune LLMs for clinical reasoning, medical question answering, and evidence-grounded generation; build verifiable reinforcement learning and foundation-model training systems, with evaluation for safety and clinical validity.
Model-written summary · the original posting is authoritative