Meta is seeking a Product Operations Manager to join our Product Operations Foundations team and drive model quality across all Meta surfaces. We are in the middle of a transformation, becoming an AI-driven, IC-led organization that scales through orchestration, deep product expertise, and technical excellence. Our team is building and operating autonomous agents that handle end-to-end workflows (triage, bug resolution, launches, dogfooding, evals) with minimal human intervention. If you're energized by owning complex quality programs end-to-end, building and operating AI-driven workflows, and driving measurable product improvements in a fast-paced environment, this role is for you. You will be responsible for investigating and communicating the quality of WhatsApp's products to engineering, product, design, and other cross-functional partners. You will own AI builds for collecting, generating, and triaging reported quality issues. Additionally, you will partner with product and engineering teams to implement process and tooling improvements focused on driving developer efficiency, resolution of issues, and improved product quality.

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

Minimum 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
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

Preferred Qualifications

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
Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
Familiarity with LLMs, AI agents, or ML evaluation frameworks
Experience in product quality, QA, or technical program management
Experience working with global/remote teams
Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
Experience operating in flat, IC-heavy org structures with high individual autonomy

$123,000/year to $179,000/year + bonus + equity + benefits

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Product Operations Manager, Model Quality