Product Operations Manager, Model Quality

Meta Careers; Los Angeles, Northern (CA, KY); Hybrid; USD 180,000 - 230,000; Full time

Job summary

Meta is seeking a Product Operations Manager for the Product Operations Foundations team to drive model quality across Meta surfaces and scale AI-driven workflows with autonomous agents. You will own end-to-end quality programs, define roadmaps for AI models, and advise leadership on investments and risk mitigation.

Expect collaboration with engineering and cross-functional partners in a fast-paced, IC-heavy environment.

Qualifications

• 7+ years of experience in strategy, operations, consulting, or data analysis.
• Experience building or deploying AI/ML solutions and evaluating models.
• Strong SQL analytics and data storytelling to influence product direction.

Responsibilities

• Set strategy for LLM models and AI workflows across product surfaces.
• Identify investment areas to improve model quality and accuracy.
• Advise leadership and define roadmaps and reporting for AI initiatives.
• Coordinate with engineering and cross-functional partners to address bottlenecks.

Skills

Data storytelling

Cross-functional influence

AI workflow design

Leadership communication

Problem decomposition

Education

Bachelor's degree in related field

Tools

SQL

AI/ML tools

Job description

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 managing and evaluating our AI solutions and infrastructure to improve precision, prevent drift, and maintain real-time observability. This role is expected to set strategy for LLM models, determine areas of investment for increasing accuracy, advise leadership on impending risks, define roadmaps and reporting strategy to shape the future of our AI work. As part of this work, you will be expected to build and maintain industry-wide expertise, develop effective cross-functional relationships, advise engineering and cross-functional partners on areas of investment, determine staffing needs, and solution against critical bottlenecks. Bachelor's degree in a directly related field, or equivalent practical experience7+ years of experience in strategy, operations, consulting, or data analysisAnalytical experience using data to tell a story and influence product direction using intermediate to advanced SQLExperience building or deploying AI/ML solutions, LLM model quality or automation in production workflowsStrong communication skills with ability to influence multiple cross-functional stakeholders and senior leadershipExperience breaking down ambiguous issues to component parts to develop solutionsAbility to design AI workflows that operate effectively within enterprise data sensitivity constraints, balancing quality and privacy principles Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologiesExperience operating in flat, IC-heavy org structures with high individual autonomyDemonstrated history of evaluating industry best practices and providing organizational recommendations on approaches to AI models and developmentExperience in product quality, QA, or technical program managementDemonstrated 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)Familiarity with LLMs, AI agents, or ML evaluation frameworksExperience working with global/remote teams