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Product Operations Manager, Model Quality

Meta· Operations
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Hybrid (Los Angeles, CA)$123k - $179kFull-timePosted 1mo ago

About the role

Product Operations Manager to join the Product Operations Foundations team to drive model quality across Meta surfaces. Responsible for managing and evaluating AI solutions and infrastructure to improve precision, prevent drift, and maintain real-time observability. Sets strategy for LLM models, advises leadership on risks, defines roadmaps and reporting strategy, and partners cross-functionally to address bottlenecks and staffing needs while building industry-wide expertise.

Responsibilities

  • Defines the technical direction for model maintenance (retraining cadences, drift mitigation, performance recovery) and evolution (new capabilities, architecture improvements, multi-modal expansion). Translates cross-product performance patterns into investment recommendations for evaluation leads
  • Provides cross-product context, defines what good looks like at the model level, and informs evaluation methodology. Evals owners own execution of verification pipelines within their products; this role ensures consistency and identifies gaps across the portfolio while building institutional competence by surfacing performance patterns and proven methodologies
  • Defines what leadership needs to see, how model health should be measured and reported, and what thresholds trigger escalation
  • Provides thought partnership to evals managers on narrative of model health, provides visibility into our classification strategy and accuracy measurement process
  • Works with evaluation managers to drive cross-app taxonomy alignment in alignment with cross-functional needs and advises on a strategy for the migration of LLM accuracy assessment to judges
  • Owns the consolidated view of all production model performance, identifies systemic patterns and emerging risks, and ensures leadership can verify model health on demand
  • Partners with AI Implementations, operational systems teams and the Metrics & Measurement team to build and maintain the infrastructure that surfaces this information
  • Establishes performance guardrails that evals captains implement. Continuously scans industry developments and best practices to incorporate into org-wide approach
  • Maintains a tight feedback loop with product and eng teams across apps to ensure alignment on production priorities and deployment risks
  • Deploys deep SME expertise to diagnose, unblock and directly resolve technical bottlenecks to complex model quality problems when evaluation leads encounter blockers they cannot resolve independently
  • Drives alignment with cross-functional teams on tooling needs to support Product Operations classification strategy (ML classification tooling for initial-tier classification, user voice, breakdown graphs) and advocates for investment, flags risks, influences direction

Qualifications

  • Bachelor's degree in a directly related field, or equivalent practical experience
  • 7+ years of experience in strategy, operations, consulting, or data analysis
  • Analytical experience using data to tell a story and influence product direction using intermediate to advanced SQL
  • Experience building or deploying AI/ML solutions, LLM model quality or automation in production workflows
  • Strong communication skills with ability to influence multiple cross-functional stakeholders and senior leadership
  • Experience breaking down ambiguous issues into component parts to develop solutions
  • Ability to design AI workflows that operate effectively within enterprise data sensitivity constraints, balancing quality and privacy principles

Skills

Required:SQLAI/ML solutionsCommunication

Benefits

  • Benefits information available in posting (not itemized here)
Last updated Oct 23, 2026. Interested? Apply on the company site.

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