--- title: 'Machine Learning Engineer at Latent' canonical: 'https://feeny.ai/job/machine-learning-engineer-latent-san-francisco-fhpj5nkjftp5' type: 'job' last_seen: '2026-10-19' --- # Machine Learning Engineer at Latent - **Company:** Latent - **Location:** San Francisco, CA - **Employment:** full-time - **Work type:** onsite - **Posted:** 2026-09-29 - **Last confirmed live:** 2026-10-19 - **Apply:** https://jobs.ashbyhq.com/latent/233bbaac-d589-49f4-a8eb-6bb16673b060 ## Job 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 high-stakes production environments - Develop evaluation frameworks to ensure model safety and clinical validity - Integrate ML systems into product workflows and patient-facing applications - Monitor system performance in production and iterate based on real-world usage and feedback - Define what “correct” means in ambiguous clinical workflows in collaboration with engineers and clinicians ## What We're Looking For - Strong foundation in machine learning and software engineering - Track record of building and owning ML systems in production where performance, reliability, or correctness materially mattered - Experience driving ambiguous ML problems from 0→1, including problem formulation, model design, and productionization - Hands-on experience with PyTorch or similar frameworks - Ability to operate independently in high-ambiguity environments with minimal guidance - Strong product and engineering judgment — you know when to use ML, when not to, and how to scope problems accordingly - Comfort working in a fast-moving, early-stage environment - Experience working on systems where decisions have real-world consequences (e.g., healthcare, finance, infrastructure) ## Nice to Have - Experience deploying LLMs in production environments - Experience building distributed systems or large-scale data pipelines - Experience working with clinical, biomedical, or other regulated datasets ## Why Join Latent - Backed by top-tier investors including General Catalyst, Conviction, and Y Combinator - Work alongside a high-caliber team building products our healthcare partners love - Work on mission-critical problems at the intersection of AI and healthcare - Real ownership and visibility - High-impact role on a small, fast-growing team ## Benefits - Competitive compensation, including meaningful equity - Medical, dental, and vision insurance for employee and dependents - Flexible PTO policy - Paid parental leave - Fertility and family-building stipend through Carrot ## About Latent ## Company Overview - **One-liner**: Latent provides an enterprise pharmacy intelligence platform that uses a clinical AI engine to automate medication access workflows—such as prior authorizations and appeals—for health systems. - **Entity Type**: Private (Series A) - **Headquarters**: San Francisco, California, United States - **Founded**: 2022 - **Founders**: Rishabh Jain and Sriram Somasundaram ## Core Business - **Primary industry/industries**: Healthcare IT, AI-powered clinical operations, pharmacy intelligence - **Target customers**: B2B; large health systems (hospitals and health networks) – currently serving over 45 partners including 50% of the top 20 U.S. health systems. - **Mission or purpose statement**: “Closing the distance between a therapeutic decision and a patient receiving therapy” by automating the manual knowledge work that sits between a doctor’s order and treatment. ## Products & Services - **Clinical Reasoning Engine**: An AI platform that performs clinical knowledge work—reasoning through patient data, interpreting drug criteria, extracting evidence, and orchestrating workflows across EHR, payers, pharmacies, and patients. Automates prior authorization, payer policy parsing, form auto-filling, and medical necessity checks. - **Pharmacy Intelligence Platform**: A suite that centralizes pharmacy operations, increases prior-authorization throughput, reduces denials, and helps pharmacists focus on patients instead of paperwork. ## Market Standing - **Valuation/Market Cap**: Not publicly available - **Key Metric**: Total funding raised – $80.5 million (Series A as of April 2026) - **Notable Investors/Partners**: Spark Capital, Transformation Capital, McKesson Ventures, Conviction, General Catalyst, Y Combinator - **Growth Signals**: - Grew from 4 to more than 45 health system partners in the past year (2025–2026) - Now serves 2 million patients annually - Reduces denials by over 30% and enables clinicians to serve twice as many patients - Customers include Yale New Haven Health, Ochsner Health, MetroHealth, UCI, Vanderbilt Health, Mount Sinai, Henry Ford Health, UCSF Health, UCLA Health ## Competitive Advantages - Deep, native integration with any EHR; the engine operates directly within the patient record. - Proprietary clinical agentic engine trained on medical reasoning, payer rules, and drug criteria – a high bar for regulatory and clinical accuracy. - Proven operational impact: 109% more prior-auth throughput per person, 23.4 minutes of every appeal handed back to pharmacists, and $300K+ annual labor cost savings cited by customers. - Already embedded in 50% of the top 20 U.S. health systems, creating a high switching cost. ## Strategic Focus - Expand health system footprint and deepen the platform connecting hospitals, payers, pharmacies, and patients. - Continue investing in reliability and trust required for healthcare deployment. - Scale the team and apply the Clinical Reasoning Engine proactively to identify patients who should start therapy and keep them on treatment. - Move beyond prior authorization into every process where clinical knowledge must be translated into action. ## Why Work Here - **Culture**: High agency, ownership, and independence; engineers own projects from ideation to completion. Values include bias to action, practical innovation, and customer obsession (regularly visiting partner sites). - **Remote/Hybrid**: Remote-friendly (headquarters in San Francisco; team is distributed). - **Notable perks/engineering culture**: Fast-moving environment with ambitious product and GTM goals; opportunity to work on one of healthcare’s hardest problems using modern AI/ML; team size ~50 (as of early 2026) – still a growth-stage startup. ## Sources 1. [latenthealth.com](https://latenthealth.com/) 2. [latenthealth.com/about](https://latenthealth.com/about) 3. [latenthealth.com/careers](https://latenthealth.com/careers) 4. [ycombinator.com/companies/latent](https://www.ycombinator.com/companies/latent) 5. [cbinsights.com/company/latent](https://www.cbinsights.com/company/latent) ## Other roles at Latent - [Security Engineer](https://feeny.ai/job/security-engineer-latent-san-francisco-or-new-york-city-58bxqak9zgpe) — San Francisco OR New York City, OR - [Head of Applied AI](https://feeny.ai/job/head-of-applied-ai-latent-san-francisco-3f9t99je7z9b) — San Francisco, CA - [Director, 340B Solutions and Partnerships](https://feeny.ai/job/director-340b-solutions-and-partnerships-latent-san-francisco-or-new-york-city-fqkdxhw0pstv) — San Francisco OR New York City, OR - [Product Marketing Lead](https://feeny.ai/job/product-marketing-lead-latent-new-york-jjbew82xm38m) — New York, NY - [Strategic Account Executive (San Francisco)](https://feeny.ai/job/strategic-account-executive-san-francisco-latent-san-francisco-p6dzkeh3qcqf) — San Francisco, CA - [Strategic Account Executive (New York City)](https://feeny.ai/job/strategic-account-executive-new-york-city-latent-new-york-ghzbpwxwwzh0) — New York, NY - [Implementation Project Manager](https://feeny.ai/job/implementation-project-manager-latent-remote-y4j1g0bskvax) - [Head of Partner Enablement](https://feeny.ai/job/head-of-partner-enablement-latent-san-francisco-or-new-york-city-6xnve4vb02zy) — San Francisco OR New York City, OR - [Clinical GTM Lead](https://feeny.ai/job/clinical-gtm-lead-latent-remote-8q7mnaxdbpxr) - [Associate Executive Business Partner (New York)](https://feeny.ai/job/associate-executive-business-partner-new-york-latent-new-york-8jdt7y8z3jjf) — New York, NY