Director, Product Management - AI/ML, Core Product

What You’ll Do

• Lead AI product strategy for Note Generation. Define the long term strategy for Abridge’s core note models and evaluation stack.
• Oversee the evaluation platform and measurement systems. Build a world class note quality evaluation system across human annotation, LLM judges, automated backtesting, and in production analytics. Partner with ML and engineering to ensure reliable benchmarks, continuous validation, and fast iteration cycles.
• Drive depth across specialties and clinical contexts. Own the specialty roadmap and ensure we prioritize specialties that drive adoption, revenue opportunities, or deeper defensibility. Ensure that specialty notes reflect clinical expectations, use the right terminology and structure, and match professional norms across care settings. Partner with clinical leaders to define gold standards and systematic approaches to specialty expansion.
• Lead and develop a team of PMs. Manage a team of product managers spanning models, quality, eval, and specialty workflow.
• Foster a culture of excellence, speed, and accountability.
• Cross functional leadership. Work closely with Engineering and ML leadership to align on architecture, model iteration schedules, evaluation methodologies, and system reliability. Partner with Product Design to define user control surfaces that leverage model outputs while keeping clinicians in control. Collaborate with customer facing teams to understand quality expectations and close the loop between real world feedback and model development.

What You’ll Bring

• 7 to 10+ years of product management experience with significant ownership of ML powered products or platform systems.
• Experience managing PMs and leading high performance product teams.
• 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 high bar for accuracy and compliance.
• You have overseen 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.