Job Description

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Latent is building the intelligence infrastructure for American healthcare. Our products are already helping hospitals and clinics dramatically increase workflow output, speed up patient access to medications, and boost provider revenue. Our flagship multimodal search and questionanswering platform analyzes EHR data to surface the most relevant information, reducing operational overhead and improving care delivery.

Were a small, missiondriven team backed by General Catalyst, Conviction, and YC, tackling some of healthcares hardest technical challenges. If youre passionate about applying cuttingedge machine learning in a highstakes domain, wed love to meet you.

About The Role

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

Youll work on some of the most pressing problems in applied AIbalancing model expressiveness with verifiability, maintaining safety in openended generation, and scaling LLMs to production in highstakes environments. This is a rare opportunity to bring research into production at the edge of whats possible in medicine and AI.

This is a highimpact, highownership role based fulltime onsite in our San Francisco office.

What Youll Do

• Train and finetune large opensource language models for clinical reasoning, medical question answering, and evidencegrounded 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 systemsfrom research prototypes to faulttolerant, privacycompliant services running in production
• Build robust retrieval pipelines for realtime 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 realworld constraints
• Contribute to a culture of ML excellence through code reviews, experimentation frameworks, and internal knowledge sharing

You Might Be a Fit If You

• Have a strong foundation in ML research or systemsthrough an advanced degree or highimpact work in industry
• Have deep experience with NLP and LLMs (e.g., finetuning, LoRA, RAG, quantization) and are comfortable with frameworks like PyTorch, Hugging Face, and LangChain
• Have shipped ML models in production environmentsespecially where latency, safety, or interpretability were critical
• Are excited by ambiguous, zerotoone problems and can think creatively about tradeoffs between performance, explainability, and reliability
• Thrive in fastmoving, ambiguous, enjoy working on openended 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 dataor are excited to learn the domain deeply

Why You Should Join Us

• Backed by top investors: General Catalyst, Conviction, and YC
• Tightknit, worldclass 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 earlystage startup with the productmarket fit of a laterstage 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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