Role Overview
The Member of Product Staff, Foundation Models & Post-Training role at Abridge involves leading the product strategy that connects machine learning research to real-world healthcare outcomes from the San Francisco office. This position suits an experienced product professional with a strong technical background who wants to bridge the gap between advanced model science and clinical product delivery.
Key Responsibilities
Establish product strategy for the company model family, making explicit decisions regarding capability, quality, latency, cost, safety, and controllability.
Define hypotheses, milestones, decision gates, and success metrics to transition models from experimental stages into shadow mode and production.
Collaborate with Data, Privacy, Security, and Clinical teams to leverage proprietary de-identified conversations, final notes, and EHR context into training signals.
Build clear frameworks for choosing between frontier models, open-source models, prompted workflows, or custom-trained models.
Partner with evaluation teams to define promotion criteria, relevant product capabilities, and critical failure modes for specific use cases.
Form a continuous learning loop by translating production failures, clinician feedback, and user behavior into actionable training priorities.
Coordinate cross-functional execution by aligning ML Science, ML Engineering, Product Engineering, Clinical Science, and product pods.
Communicate intricate research choices clearly to executive leadership and various product teams.
Requirements
Seven or more years of product management or closely related experience, featuring substantial ownership of machine learning products, model platforms, or artificial intelligence infrastructure.
Demonstrated success in translating ambiguous technical capabilities into shipped products that deliver measurable user and business outcomes.
Working knowledge of the modern model development lifecycle, covering data strategy, fine-tuning, preference optimization, evaluation, inference, experimentation, and production monitoring.
Technical judgment to engage in discussions with machine learning scientists and engineers regarding training objectives, reward design, data quality, and serving costs.
Product judgment to identify where proprietary models create durable differentiation compared to external models or traditional systems.
Experience establishing clarity across multiple teams by defining decision rights, sequencing dependencies, and resolving disagreements.
High standards for evidence, safety, and trust, acknowledging that clinical artificial intelligence requires human review paths and escalation protocols.
Excellent written and verbal communication skills tailored for both technical research groups and company executives.
Nice to Have
Direct work history involving LLM post-training, reinforcement learning, preference optimization, distillation, model routing, or domain-adaptive pretraining.
Experience managing portfolios that span frontier APIs, open-source models, and in-house models.
Background working with human-feedback or expert-annotation systems, particularly when feedback is sparse or subjective.
Experience shipping artificial intelligence in healthcare, life sciences, or other safety-critical regulated industries.
Familiarity with clinical documentation, medical reasoning, agentic workflows, or longitudinal context.
Past partnerships with research teams on high-compute initiatives that required staged evidence prior to scaling investment.
Skills and Tools
Large Language Models (LLMs)
Machine Learning Lifecycle Management
Data Strategy and Governance
Model Evaluation and Preference Optimization
Cross-functional Leadership
Product Strategy and Portfolio Management
Salary and Benefits
Annual salary range between $250,000 and $290,000 USD
Generous time off including 14 paid holidays, flexible paid time off for salaried employees, and accrued time off for hourly workers
Comprehensive medical, dental, and vision health plans for full-time employees and their families
Monthly company contributions toward a Health Savings Account (HSA) when selecting a High Deductible Health Plan
Paid parental leave and family-forming benefits providing financial support and resources
401(k) retirement plan contribution matching
Tax-free personal device allowance and pre-tax flexible spending accounts and commuter benefits
Lifestyle wallet providing monthly contributions for fitness, professional development, and coworking spaces
Dedicated mental health support offering therapy and coaching resources
Paid sabbatical leave following five years of continuous employment
Competitive compensation packages and equity grants for full-time employees
About the Company
Abridge was founded in 2018 with the mission of powering deeper understanding in healthcare through an AI-powered platform purpose-built for medical conversations. The technology transforms patient-clinician interactions into structured clinical notes in real time with deep EMR integrations, allowing clinicians to focus primarily on patient care. Operating as a growing team of practicing medical doctors, artificial intelligence scientists, PhDs, technologists, and engineers, the company maintains offices in San Francisco, New York, and Pittsburgh.
How to Apply
Interested candidates should visit the official company careers page to submit their application for this opportunity.
