Machine Learning Engineer

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Machine Learning Engineer

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Latent

Latent is building the intelligence infrastructure for American healthcare. Our flagship multi-modal search and question-answering platform analyzes EHR data to surface the most relevant information, reducing operational overhead and improving care delivery.

We’re a small, mission-driven team backed by General Catalyst, Conviction, and YC, tackling some of healthcare’s hardest technical challenges. If you're passionate about applying cutting-edge machine learning in a high-stakes domain, we’d love to meet you.

About The Role

As a Machine Learning Engineer at Latent, you’ll design and deploy advanced models at the frontier of medical language understanding. You will develop systems that can interpret long-form clinical text, generate auditable justifications for medical decisions, and reason over structured and unstructured data to automate the prior authorization process end-to-end.

You’ll work on some of the most pressing problems in applied AI—balancing model expressiveness with verifiability, maintaining safety in open-ended generation, and scaling LLMs to production in high-stakes environments. This is a rare opportunity to bring research into production at the edge of what’s possible in medicine and AI.

This is a high-impact, high-ownership role based full-time onsite in our San Francisco office.

What You’ll Do

Train and fine-tune large open-source language models for clinical reasoning, medical question answering, and evidence-grounded generation, where the stakes are human health

Design and scale multimodal embeddings to encode clinical documents, structured EHRs, and payer policies in a unified space

Own the lifecycle of ML systems—from research prototypes to fault-tolerant, privacy-compliant services running in production

Build robust retrieval pipelines for real-time semantic search and RAG architectures in the clinical domain

Collaborate with clinicians, engineers, and product leaders to ensure outputs are interpretable, auditable, and aligned with real-world constraints

You Might Be a Fit If You

Have a strong foundation in ML research or systems—through an advanced degree or high-impact work in industry

Have deep experience with NLP and LLMs (e.g., fine-tuning, LoRA, RAG, quantization) and are comfortable with frameworks like PyTorch, Hugging Face, and LangChain

Have shipped ML models in production environments—especially where latency, safety, or interpretability were critical

Are excited by ambiguous, zero-to-one problems and can think creatively about tradeoffs between performance, explainability, and reliability

Thrive in fast-moving, ambiguous, open-ended technical challenges, and work well with minimal oversight

Bonus : Have published ML research or contributed to the broader ML community

Bonus : Have worked with clinical, biomedical, or claims data—or are excited to learn the domain deeply

Compensation

The expected Pay Scale is $165,000-250,000 annually, in addition to equity and comprehensive benefits. Compensation packages are highly variable based on a variety of factors including experience and expertise. If your compensation expectations fall outside this range, we still encourage you to apply.

Why You Should Join Us

Backed by top investors : General Catalyst, Conviction, and YC

Tight-knit, world-class team with a deep sense of mission

Huge greenfield opportunity with significant ownership and room for growth

Competitive salary and equity compensation. The equity upside of an early-stage startup with the product-market fit of a later-stage company.

Excellent benefits and versatile health, dental, and vision coverage plans

Paid parental leave

Lunch and dinner provided at the office

Unlimited PTO

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