Machine Learning Engineer

Latent • San Francisco, CA

16d • Onsite

About The Position

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.

Requirements

• 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, enjoy working on open-ended technical challenges, and work well with minimal oversight

Nice To Haves

• Have published ML research or contributed to the broader ML community
• Have worked with clinical, biomedical, or claims data—or are excited to learn the domain deeply

Responsibilities

• 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
• Contribute to a culture of ML excellence through code reviews, experimentation frameworks, and internal knowledge sharing

Benefits

• 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

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed