Product Lead, Foundational Models and Post-Training

Abridge
San Francisco
Workplace: HybridFull timeUSD 250,000 - 290,000 annuallyFunction: Product ManagementSkills: ["Cross-functional leadership","Written communication","Verbal communication","Evidence-based decision-making","Strategic thinking"]

Own product strategy for a family of foundational and post-training models, translating priorities into a portfolio spanning capability, quality, latency, cost, safety, and controllability. Lead the research-to-production path with decision gates and success metrics, turning proprietary clinical conversation and EHR signals into training advantages. Partner across ML Science, engineering, Evals, and clinical teams to create durable, evidence-based model improvements for clinician value, patient safety, and measurable business impact.

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FursaFursa
Abridge
Abridge
1 day ago

Product Lead, Foundational Models and Post-Training

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Last checked: 2 hours agoStatus: Live

Job Summary

Own product strategy for a family of foundational and post-training models, translating priorities into a portfolio spanning capability, quality, latency, cost, safety, and controllability. Lead the research-to-production path with decision gates and success metrics, turning proprietary clinical conversation and EHR signals into training advantages. Partner across ML Science, engineering, Evals, and clinical teams to create durable, evidence-based model improvements for clinician value, patient safety, and measurable business impact.
Location: San Francisco
Workplace: Hybrid
Employment Type: Full time
Job Function: Product Management
Seniority: Mid level

Key Responsibilities

  • •Set product strategy for the model family, defining explicit portfolio choices across capability, quality, latency, cost, safety, and controllability.
  • •Own the path from research to product impact by defining hypotheses, milestones, decision gates, and success metrics through shadow mode to production.
  • •Shape how proprietary clinical conversation and EHR signals (including clinician edits and care actions) are used as training and feedback signals.
  • •Build legible model investment frameworks for when to use different model types and quantify quality, serving cost, latency, control, and strategic benefits.
  • •Drive cross-functional execution with ML Science, engineering, Evals, and clinical teams, often without formal authority, and communicate strategy to leadership.

Pay and Benefits

Salary: USD 250,000 - 290,000 annually
Equity and Bonus:Equity
Perks:Health InsuranceDentalVisionPaid LeaveParental Leave401kHsa ContributionLearning BudgetCommuter Benefits

Key Requirements

  • •7+ years of product-management or closely related experience with substantial ownership of ML-powered products, model platforms, or AI infrastructure.
  • •Track record turning ambiguous technical capabilities into shipped products with measurable user or business outcomes.
  • •Strong knowledge of the model-development lifecycle, including data strategy, fine-tuning/preference optimization, evaluation, inference, experimentation, and production monitoring.
  • •Technical judgment to discuss training objectives, reward design, data quality, model selection, scaling, latency, and serving cost with ML scientists and engineers.
  • •High bar for evidence, safety, and trust in clinical AI, including escalation/abstention/human-review paths.
Experience:HealthcareAI infrastructureMachine learningLLMsGenerative AI
Skills:Cross-functional leadershipWritten communicationVerbal communicationEvidence-based decision-makingStrategic thinking
Tech Stack:EHR integrationsEMRDe-identified conversationsFine-tuningPreference optimizationEvaluationInferenceExperimentationProduction monitoringReinforcement learningReinforcement learning (post-training)Preference optimization (post-training)Model routing

Company Brief

Abridge
Builds an enterprise-grade generative-AI platform that captures and summarizes patient–clinician conversations in real time to produce structured clinical documentation, integrated with EMRs to reduce clinician documentation burden and enable clinical and revenue workflows.
Industry: HealthTech
Company Size: Large (251 to 1,000 employees)
Growth: Scaleup
Valuation: Unicorn (USD 1B+)
Funding: Series E+
Headquarters: San Francisco, United States
Founded: 2018
Glassdoor
Glassdoor: 4.7
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