Machine Learning Engineer

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 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 RoleAs 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 DoTrain and fine-tune large open-source language models for clinical reasoning, medical question answering, and evidence-grounded generation, where the stakes are human healthDesign and scale multimodal embeddings to encode clinical documents, structured EHRs, and payer policies in a unified spaceOwn the lifecycle of ML systems—from research prototypes to fault-tolerant, privacy-compliant services running in productionBuild robust retrieval pipelines for real-time semantic search and RAG architectures in the clinical domainCollaborate with clinicians, engineers, and product leaders to ensure outputs are interpretable, auditable, and aligned with real-world constraintsContribute to a culture of ML excellence through code reviews, experimentation frameworks, and internal knowledge sharingYou Might Be a Fit If You…Have a strong foundation in ML research or systems—through an advanced degree or high-impact work in industryHave deep experience with NLP and LLMs (e.g., fine-tuning, LoRA, RAG, quantization) and are comfortable with frameworks like PyTorch, Hugging Face, and LangChainHave shipped ML models in production environments—especially where latency, safety, or interpretability were criticalAre excited by ambiguous, zero-to-one problems and can think creatively about tradeoffs between performance, explainability, and reliabilityThrive in fast-moving, ambiguous, enjoy working on 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 deeplyCompensationThe expected salary range for this role is $140,000 to $240,000 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 UsBacked by top investors: General Catalyst, Conviction, and YCTight-knit, world-class team with a deep sense of missionHuge greenfield opportunity with significant ownership and room for growthCompetitive 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 plansPaid parental leaveLunch and dinner provided at the officeUnlimited PTOCreate a Job AlertInterested in building your career at Latent? 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Created: 2025-09-17