Machine Learning Engineer

# Machine Learning Engineer Latent San  Francisco Full-time $225,000 – $300,000 / yearAI tools:

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You’ll own production machine-learning systems that support clinical workflows, from problem definition and modeling through deployment and monitoring. The work includes training and evaluating language models for clinical reasoning and evidence-grounded responses, with decisions that can affect patient outcomes.
* Permanent* On-site
* Senior / Staff### Skills and expertise

PyTorch large language models reinforcement learning model fine-tuning model evaluation production ML systems data pipelines clinical data### Key responsibilities
* Own end-to-end ML systems, from architecture and modeling through production infrastructure.
* Train and fine-tune language models for clinical reasoning and evidence-grounded generation.
* Build safety and clinical-validity evaluations, then monitor systems in production.## How this job compares

Compared with 410 open senior machine learning jobs on October 10, 2026.Pay:
This job pays $225K to $300K a year. The 143 open senior machine learning jobs that publish US pay start at $186K on average, so this job starts about 21% higher.

Similar open jobs:
We Love AI Jobs lists 410 open senior machine learning jobs at 176 companies.

Remote work:
This job is on site. 90 of the 410 senior machine learning jobs (22%) are remote.

AI in this role:
High. AI is the core of the work: building, training or deploying AI systems. The core work is building, training, fine-tuning, and evaluating language models for clinical workflows. The posting specifically calls out production ML systems and model safety evaluation.## Full description

About Latent Latent is the enterprise pharmacy intelligence platform, powered by a clinical agentic engine, that enables health systems to grow their pharmacy operations and serve more patients. One engine works across the pharmacy journey to identify patients who qualify for care, improve medication access, capture eligible prescriptions and support patients throughout treatment. Latent’s platform enables more than 60 leading health systems that collectively serve an estimated 70 million people.

Founded by Sriram “Sri” Somasundaram and Rishabh Jain, Latent has raised $80 million from Transformation Capital, Spark Capital, Conviction, General Catalyst, Y Combinator, and others.

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…