Member of Product Staff, AI/ML (Evals) at Abridge in SF Office

Job description

About Abridge Founded in 2018, Abridge is the first AI-native clinician intelligence platform organized around the patient, built for clinicians, and designed to help health systems coordinate the clinical, financial, and evidence-based decisions for every moment of care. Powered by purpose-built AI for healthcare, Abridge connects patients, providers, payers, and life sciences companies. This year, the platform will support more than 100 million patient-clinician conversations across more than 300 of the largest and most complex health systems in the U.S. With deep workflow integration, the Abridge clinician intelligence platform has been validated to support encounters in 28+ languages across specialties and care settings. Abridge is setting the industry standard for the responsible deployment of Al across health systems with continual and transparent Al evaluation. Clinical decision support references and cites gold-standard sources of evidence, and features like Linked Evidence map AI-generated documentation to source data, helping clinicians quickly trust and verify the output. Abridge was awarded Best in KLAS for Ambient AI in 2025 and 2026, in addition to other accolades, including TIME Best Inventions of 2024 and 2025, CNBC Disruptor 2025, and Fast Company’s Most Innovative Companies 2025. We are a growing team of practicing clinicians, AI scientists, PhDs, creatives, technologists, and engineers working together to transform healthcare. We have offices located in San Francisco, New York, and Pittsburgh. The Role Abridge's has multiple products - the core product is ambient clinical notes, but we’ve expanded surfaces: billing, clinical decision support, orders, nursing, etc. Measuring quality reliably and iterating fast without breaking clinician trust sit at the core of every single product’s success. The Evals team owns the tooling, templates, and consultation that product teams use across the eval lifecycle: curate, build, iterate, and deploy. This builds the strategy, platform, and process that enables evals to be fast, trustworthy, consistent, and a true moat. We are hiring a Product Manager to lead this platform. You will work with 10+ teams and partner closely with engineering, ML, data science, and clinician science. You will help set the standard for how Abridge measures AI quality, decide what the platform builds, and make evaluating a new model cheap and routine as frontier models ship frequently. What You'll Do Drive product strategy and execution for the evals platform. Own the roadmap across the eval lifecycle and own outcomes against it. Build the shared measurement infrastructure. Help build the systems that let any pod define quality, run experiments, compare models, and watch production. Own the standards for LLM judges, rule-based evaluators, human annotation, and online monitoring, and be clear about where each belongs. Make model selection fast and routine. Give teams a repeatable way to evaluate a new frontier model within days of release, and a defensible framework for when a post-trained specialty model is worth it over a prompted frontier one. Keep the eval system model-agnostic so it stays a neutral referee. Own the operating model across pods. Define the eval gates from early build through GA and steady-state monitoring, which gates are hard versus advisory, and who owns non-negotiable floors like critical-error rates. Land this across pods you don't own, without formal authority. Cross functional execution. Work with Data Engineering on the de-identification pipeline, Data Science on bootstrapping judge quality with less human annotation, Clinical Science on flagged production cases, and the agent platform team as workflows go agentic. Operate with a high bar for quality, speed, and accountability. What You Bring 5+ years of product management experience with significant ownership of ML powered products or platform systems. Deep understanding of how to measure and improve model quality, incl