Machine Learning Engineer

About LatentLatent 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 RoleThe 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 DoOwn end-to-end ML systems, including architecture, data, modeling, evaluation, and production infrastructureTrain and fine-tune large language models (LLMs) for:Clinical reasoningMedical question answeringEvidence-grounded generationMake and own tradeoffs across accuracy, latency, cost, and safety in high-stakes production environmentsDevelop evaluation frameworks to ensure model safety and clinical validityIntegrate ML systems into product workflows and patient-facing applicationsMonitor system performance in production and iterate based on real-world usage and feedbackDefine what “correct” means in ambiguous clinical workflows in collaboration with engineers and clinicians What We're Looking ForStrong foundation in machine learning and software engineeringTrack record of building and owning ML systems in production where performance, reliability, or correctness materially matteredExperience driving ambiguous ML problems from 0→1, including problem formulation, model design, and productionizationHands-on experience with PyTorch or similar frameworksAbility to operate independently in high-ambiguity environments with minimal guidanceStrong product and engineering judgment — you know when to use ML, when not to, and how to scope problems accordinglyComfort working in a fast-moving, early-stage environmentExperience working on systems where decisions have real-world consequences (e.g., healthcare, finance, infrastructure)Nice to HaveExperience deploying LLMs in production environmentsExperience building distributed systems or large-scale data pipelinesExperience working with clinical, biomedical, or other regulated datasets Why Join Latent Backed by top-tier investors including General Catalyst, Conviction, and Y CombinatorWork alongside a high-caliber team building products our healthcare partners loveWork on mission-critical problems at the intersection of AI and healthcareReal ownership and visibilityHigh-impact role on a small, fast-growing teamBenefitsCompetitive compensation, including meaningful equityMedical, dental, and vision insurance for employee and dependentsFlexible PTO policyPaid parental leaveFertility and family-building stipend through Carrot