About Abridge
Abridge was founded in 2018 with the mission of powering deeper understanding in healthcare. Our AI-powered platform was purpose-built for medical conversations, improving clinical documentation efficiencies while enabling clinicians to focus on what matters most—their patients.
Our enterprise-grade technology transforms patient-clinician conversations into structured clinical notes in real-time, with deep EMR integrations. Powered by Linked Evidence and our purpose-built, auditable AI, we are the only company that maps AI-generated summaries to ground truth, helping providers quickly trust and verify the output. As pioneers in generative AI for healthcare, we are setting the industry standards for the responsible deployment of AI across health systems.
We are a growing team of practicing MDs, AI scientists, PhDs, creatives, technologists, and engineers working together to empower people and make care make more sense. We have offices located in the Mission District in San Francisco, the SoHo neighborhood of New York, and East Liberty in 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, including evaluation frameworks, annotation pipelines, and benchmark design.
Strong technical fluency across ML, data pipelines, and distributed systems.
Experience working closely with ML researchers and engineers to drive impact in production.
Ability to balance long term architectural investments with near term quality improvements.
Strong communication skills and the ability to translate complex technical concepts into clear decisions and narratives.
A track record of delivering high quality products in domains where accuracy, reliability, and trust are paramount.
Bonus Points If…
You have experience building evaluation platforms, ML observability systems, or quality measurement pipelines.
You have worked in clinical, healthcare, or regulated environments with a high bar for accuracy and compliance.
You have worked on specialty specific or domain specific model adaptations.
You have worked on personalization systems, context ingestion frameworks, or ambient intelligence products.
You have experience shipping large scale ML products with human in the loop workflows.
Why Work at Abridge?
At Abridge, we’re transforming healthcare delivery experiences with generative AI, enabling clinicians and patients to connect in deeper, more meaningful ways. Our mission is clear: to power deeper understanding in healthcare. We’re driving real, lasting change, with millions of medical conversations processed each month.
Joining Abridge means stepping into a fast-paced, high-growth startup where your contributions truly make a difference. Our culture requires extreme ownership—every employee has the ability to (and is expected to) make an impact on our customers and our business.
Beyond individual impact, you will have the opportunity to work alongside a team of curious, high-achieving people in a supportive environment where success is shared, growth is constant, and feedback fuels progress. At Abridge, it’s not just what we do—it’s how we do it. Every decision is rooted in empathy, always prioritizing the needs of clinicians and patients.
We’re committed to supporting your growth, both professionally and personally. Whether it's flexible work hours, an inclusive culture, or ongoing learning opportunities, we are here to help you thrive and do the best work of your life.
If you are ready to make a meaningful impact alongside passionate people who care deeply about what they do, Abridge is the place for you.
How we take care of Abridgers:
Generous Time Off: 14 paid holidays, flexible PTO for salaried employees, and accrued time off for hourly employees
Comprehensive Health Plans: Medical, Dental, and Vision coverage for all full-time employees and their families.
Generous HSA Contribution: If you choose a High Deductible Health Plan, Abridge makes monthly contributions to your HSA.
Paid Parental Leave: Generous paid parental leave for all full-time employees.
Family Forming Benefits: Resources and financial support to help you build your family.
401(k) Matching: Contribution matching to help invest in your future.
Personal Device Allowance: Tax free funds for personal device usage.
Pre-tax Benefits: Access to Flexible Spending Accounts (FSA) and Commuter Benefits.
Lifestyle Wallet: Monthly contributions for fitness, professional development, coworking, and more.
Mental Health Support: Dedicated access to therapy and coaching to help you reach your goals.
Sabbatical Leave: Paid Sabbatical Leave after 5 years of employment.
Compensation and Equity: Competitive compensation and equity grants for full time employees.
... and much more!
Equal Opportunity Employer
Abridge is an equal opportunity employer and considers all qualified applicants equally without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran status, or disability.
We're committed to providing reasonable accommodations throughout the interview process. Once you submit your application, we'll follow up with details on how to request an accommodation for interviewing, completing any assessments, or otherwise participating in the selection process.
Staying safe - Protect yourself from recruitment fraud
We are aware of individuals and entities fraudulently representing themselves as Abridge recruiters and/or hiring managers. Abridge will never ask for financial information or payment, or for personal information such as bank account number or social security number during the job application or interview process. Any emails from the Abridge recruiting team will come from an @abridge.com email address. You can learn more about how to protect yourself from these types of fraud by referring to this article. Please exercise caution and cease communications if something feels suspicious about your interactions.