Machine Learning Engineer
$225k - $300k • San Francisco • FullTime
Posted 19d ago
Job Location
San Francisco
Tech Stack
Remote Work Policy
On-site
Employment Type
FullTime
Categories
Machine Learning Engineer
About the job
Latent is seeking a Machine Learning Engineer to join their team and build systems that run in real clinical workflows. This role involves owning the design, development, and operation of production-grade ML systems from ambiguous problem definition through to reliable production deployment. The ideal candidate will drive systems end-to-end, setting technical direction and taking ownership of critical systems that directly impact real patient outcomes. This is an opportunity to work on mission-critical problems at the intersection of AI and healthcare within a fast-growing, early-stage company backed by top-tier investors.
Responsibilities
- Own end-to-end ML systems, including architecture, data, modeling, evaluation, and production infrastructure.
- Train and fine-tune large language models (LLMs) for clinical reasoning, medical question answering, and evidence-grounded generation.
- Make and own tradeoffs across accuracy, latency, cost, and safety in high-stakes 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 and feedback.
- 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 where performance, reliability, or correctness materially mattered.
- Experience driving ambiguous ML problems from 0→1, including problem formulation, model design, and productionization.
- Hands-on experience with PyTorch or similar frameworks.
- Ability to operate independently in high-ambiguity environments with minimal guidance.
- Strong product and engineering judgment.
- Comfort working in a fast-moving, early-stage environment.
- Experience working on systems where decisions have real-world consequences (e.g., healthcare, finance, infrastructure).
Benefits
- Competitive compensation, including meaningful equity
- Medical, dental, and vision insurance for employee and dependents
- Flexible PTO policy
- Paid parental leave
- Fertility and family-building stipend through Carrot