Product Operations Manager, Model Quality

Meta is a technology company building products that help people connect, find communities, and grow businesses. Meta seeks a Product Operations Manager to drive model quality across its products by defining model health standards, building AI-driven quality workflows, and coordinating evaluation and performance improvements. The role partners with product, engineering, design, and cross-functional teams to resolve technical bottlenecks, improve tooling, and manage production model risks.

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 evals captains
• Provides cross-product context, defines what good looks like at the model level, and informs eval methodology. Evals captains 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, enabling evals captains' ability to execute and unblocking them as needed
• Defines what leadership needs to see, how model health should be measured and reported, and what thresholds trigger escalation
• Provides thought partnership to evals captains on narrative of model health, provides visibility into our classification strategy and accuracy measurement process
• Works with Evals captains to drive cross app taxonomy alignment in alignment with XFN needs and develops a strategy and lead the execution of the migration of our 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 (atrophy, accuracy regressions, performance plateaus) when captains hit walls they cannot resolve independently
• Drives alignment with XFN and cross functional teams (quality and reliability partner teams) on tooling needs to support Prod Ops classification strategy (ML classification tooling for L0, user voice, breakdown graphs). Advocates for investment, flags risks, influences direction

Requirements:

• 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
• Proactive problem solver with experience breaking down ambiguous issues into component parts to develop solutions
• Experience with WhatsApp or similar messaging/communication platforms, with understanding of mobile-first product behaviors, encryption, and multi-platform feature parity
• Ability to design AI workflows that operate effectively within WhatsApp's data sensitivity constraints, balancing quality signal collection with privacy-first principles and encryption guardrails
• Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
• Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
• Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
• Prior experience working on or with WhatsApp or comparable large-scale messaging products
• Familiarity with LLMs, AI agents, or ML evaluation frameworks
• Experience in product quality, QA, or technical program management
• Experience working with global/remote teams
• Experience operating in flat, IC-heavy org structures with high individual autonomy