--- title: 'Research Scientist at Latent' canonical: 'https://feeny.ai/job/research-scientist-latent-san-francisco-kfxqg1cckaxn' type: 'job' last_seen: '2026-09-14' --- # Research Scientist at Latent - **Company:** Latent - **Location:** San Francisco, CA - **Employment:** full-time - **Work type:** onsite - **Posted:** 2026-04-13 - **Last confirmed live:** 2026-09-14 - **Apply:** https://jobs.ashbyhq.com/latent/648fa6e1-52b8-4c43-8cf9-ab80260ecb1d ## Job description Research Scientist ## About Latent Health Healthcare today is only truly personalized for two groups: those with wealth and access, and those with physicians in their immediate family. For everyone else, care is fragmented and impersonal. Medical history is scattered across systems that don’t communicate. Physicians have minutes to understand decades of context. And when something goes wrong, patients are left with tools that understand medicine broadly—but not the individual. We believe this can be fundamentally rebuilt. At Latent Health, we are building systems that understand both: - the population (clinical knowledge at scale) - and the individual (longitudinal patient history) Our models are designed to answer complex clinical questions with patient-specific context and verifiable reasoning. Our dataset represents one of the most clinically diverse populations in the United States, including patients with chronic illness and complex disease. Each patient record contains extraordinary depth. ML at Latent Health 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 - 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. We are a small team and expect engineers to take ownership of critical systems, not components. ## The Role As a Machine Learning Engineer, Research, you will own the design and development of novel modeling approaches that advance state-of-the-art clinical intelligence. You will drive research from ambiguous problem definition through to validated results and downstream impact, shaping the technical direction of how models learn from longitudinal patient data. We are primarily hiring for senior and staff-level engineers who are comfortable owning critical research problems end-to-end. This role involves working on problems that directly impact real patient outcomes. ## What You’ll Do - Own research initiatives end-to-end, including problem formulation, experimental design, modeling, and evaluation - Develop novel architectures, training methods, and objectives leveraging longitudinal patient data - Work on verifiable reinforcement learning, mid-training, and post-training of foundation models - Design rigorous evaluation methodologies to assess model reasoning, correctness, and clinical relevance - Make and own tradeoffs between model capability, interpretability, and verifiability in high-stakes settings - Collaborate with clinicians and engineers to define meaningful problem formulations grounded in real-world workflows - Partner with ML engineers to ensure research translates into deployable systems ## What We’re Looking For - Strong foundation in machine learning, deep learning, or a related technical field - Track record of driving ML research or novel modeling work from idea to validated results - Experience working on ambiguous research problems with limited prior art - Hands-on experience with PyTorch or similar frameworks - Ability to operate independently in high-ambiguity environments with minimal guidance - Strong technical judgment — you can identify meaningful problems, design appropriate approaches, and evaluate results rigorously - 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 - Publications at top-tier ML venues (e.g., NeurIPS, ICML, ICLR) - Experience with LLMs, NLP, or sequence modeling - Experience with reinforcement learning or alignment methods - Experience working with longitudinal or structured data at scale - Experience working with clinical, biomedical, or scientific domains ## Why Join Latent Health - Work on high-stakes problems with real impact on patient care - Build systems that define how AI is trusted in clinical decision-making - Significant ownership in a small, high-caliber team - Competitive compensation and meaningful equity Location We are based in San Francisco and work together in person. We spend most of the week in the office and prioritize candidates who are excited to work this way. ## Compensation - Base salary: $225,000 – $300,000+ - Meaningful equity in an early-stage, Series A company Closing If you’re interested in building systems that bring truly personalized healthcare to millions of patients, we’d love to talk. ## 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 - [Strategic Finance](https://feeny.ai/job/strategic-finance-latent-san-francisco-ns6s88ztkyfg) — San Francisco, CA - [Recruiting Coordinator](https://feeny.ai/job/recruiting-coordinator-latent-san-francisco-3tkhhwschbza) — San Francisco, CA - [Manager, Business Development Representatives](https://feeny.ai/job/manager-business-development-representatives-latent-new-york-thndt41fqm2y) — New York, NY - [Regional VP of Sales](https://feeny.ai/job/regional-vp-of-sales-latent-san-francisco-0xvvks4xzpas) — San Francisco, CA - [Strategic Account Executive](https://feeny.ai/job/strategic-account-executive-latent-new-york-vsjm76yzdckt) — New York, NY - [Sales Development Representative](https://feeny.ai/job/sales-development-representative-latent-san-francisco-gyxeqv64vnv3) — San Francisco, CA - [Eng Manager](https://feeny.ai/job/eng-manager-latent-san-francisco-y335vgksa8rt) — San Francisco, CA - [Clinical Informatics Specialist](https://feeny.ai/job/clinical-informatics-specialist-latent-san-francisco-0q42d8e91tbc) — San Francisco, CA - [Senior Customer-Led Growth Manager](https://feeny.ai/job/senior-customer-led-growth-manager-latent-new-york-9bagz7djsdmv) — New York, NY - [Senior Product Marketing Manager](https://feeny.ai/job/senior-product-marketing-manager-latent-new-york-jjbew82xm38m) — New York, NY