Machine Learning Engineer

Latent Space; San Francisco (CA); On-site; USD 170,000 - 210,000; Full time

Benefits offered by this job

Equity

Medical insurance

Dental insurance

Vision insurance

Flexible PTO

Parental leave

Fertility stipend

Job summary

Latent is the enterprise pharmacy intelligence platform accelerating prior authorizations, appeals, and 340B compliance to get patients started on therapy faster. As a Machine Learning Engineer, you will own the design, development, and operation of production-grade ML systems that run in real clinical workflows, driving deployment from ambiguity to reliable production systems.

We are a small, high-ownership team delivering systems that directly impact patient outcomes in healthcare AI.

Qualifications

• Experience deploying ML systems in production with measurable impact.
• Hands-on with PyTorch or similar frameworks.
• Ability to work independently in high-ambiguity environments with minimal guidance.

Responsibilities

• Own end-to-end ML systems from architecture to production deployment.
• Train and fine-tune LLMs for clinical reasoning and medical QA.
• Develop evaluation frameworks for safety and clinical validity.
• Integrate ML systems into product workflows and patient-facing apps.
• Monitor production performance and iterate from real usage.
• Define what “correct” means in collaboration with engineers and clinicians.

Skills

Machine learning

Software engineering

Production systems

Independent work

Tools

PyTorch

Job description

About Latent

Latent is the enterprise pharmacy intelligence platform. Our clinical AI streamlines prior authorizations, appeals, and 340B compliance, so patients start therapy faster and care teams spend less time on paperwork.

We raised an $80M Series A led by Spark Capital and Transformation Capital, with General Catalyst, McKesson Ventures, Conviction, and Y Combinator. 60+ health systems run on Latent, including Yale New Haven, Mount Sinai, UCSF, and Ochsner. We move fast, operate with high ownership, and build products that directly improve patient care.

The Role

The Machine Learning team is responsible for building systems that run in real clinical workflows. We work on verifiable reinforcement learning at scale, mid-training and post-training of foundation models, and novel objectives derived from longitudinal patient data. We are a small group of researchers and engineers focused on pushing the frontier while shipping real systems into production, and we expect engineers to take ownership of critical systems, not components.

As a Machine Learning Engineer, you will own the design, development, and operation of production-grade ML systems that run in real clinical workflows. You will drive systems from ambiguous problem definition through to reliable production deployment, setting technical direction along the way. We are primarily hiring for senior and staff-level engineers who are comfortable owning critical systems end-to-end. This role involves owning systems that directly impact real patient outcomes.

What You'll Do

• 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

  • 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

What We're Looking For

• 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 — you know when to use ML, when not to, and how to scope problems accordingly

• Comfort working in a fast-moving, early-stage environment

• Experience working on systems where decisions have real-world consequences (e.g., healthcare, finance, infrastructure)

Nice to Have

• Experience deploying LLMs in production environments

• Experience building distributed systems or large-scale data pipelines

• Experience working with clinical, biomedical, or other regulated datasets

Why Join Latent

• Backed by top-tier investors including General Catalyst, Conviction, and Y Combinator

• Work alongside a high-caliber team building products our healthcare partners love

• Work on mission-critical problems at the intersection of AI and healthcare

• Real ownership and visibility

• High-impact role on a small, fast-growing team

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