Director, Product Management - Ai/ml, Core Product

Abridge · Vertical AI · San Francisco, CA · Builder

Product leader to define the vision, strategy, and execution for Abridge's core note generation models and evaluation stack. This role will manage a team of PMs and partner with engineering, ML, design, and clinical leaders to set the bar for note quality, guide the model and evaluation roadmap, and deliver key capabilities for the market. The role emphasizes leading AI product strategy, overseeing the evaluation platform and measurement systems, driving depth across specialties, and leading/developing a team of PMs.

What you'd actually do

  1. Lead AI product strategy for Note Generation.
  2. Oversee the evaluation platform and measurement systems.
  3. Drive depth across specialties and clinical contexts.
  4. Lead and develop a team of PMs.
  5. Foster a culture of excellence, speed, and accountability.

Skills

Required

  • 7 to 10+ years of product management experience
  • 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

Nice to have

  • Experience building evaluation platforms, ML observability systems, or quality measurement pipelines
  • Worked in clinical, healthcare, or regulated environments with high bar for accuracy and compliance
  • Oversaw specialty specific or domain specific model adaptations
  • Worked on personalization systems, context ingestion frameworks, or ambient intelligence products
  • Experience shipping large scale ML products with human in the loop workflows

What the JD emphasized

  • 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
  • A track record of delivering high quality products in domains where accuracy, reliability, and trust are paramount

Other signals

  • owns the models that power documentation
  • evaluation systems that measure quality at scale
  • specialty and workflow engines
  • product leader to lead the product vision, strategy, and execution for Note Generation
  • manage a team of PMs and partner closely with engineering, ML, design, clinical leaders
  • set the bar for note quality
  • guide our model and evaluation roadmap
  • deliver the table stakes and differentiated capabilities required to win the market