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Data Annotation Program Manager Jobs in California

Experience analyzing LiDAR point clouds, video, and image annotation data. * Ability to manage ... Purchase Program if you meet certain eligibility requirements. Full‑time employee coverage is ...

The role As the Lead Technical Program Manager for Data at Wayve, you'll build and lead the ... Data platform, data pipelines, enrichment & curation, labelling / annotation, and dataset ...

... annotation programs. * Experience managing QA operations, calibration sessions, audits, and quality improvement initiatives. * Familiarity with annotation tools and AI data workflows. * Experience ...

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Data Annotation Program Manager information

What is a data annotation program manager?

Data Annotation Program Managers are professionals who oversee and coordinate data labeling projects, ensuring that data used for machine learning and artificial intelligence is accurately tagged and prepared. They manage teams of annotators, set project guidelines, monitor quality, and ensure deadlines are met. Their role is crucial for building high-quality datasets that enable reliable AI model training. Program Managers often collaborate with data scientists, engineers, and stakeholders to define requirements and improve annotation processes.

How does a data annotation program manager coordinate with cross-functional teams to ensure project success?

A Data Annotation Program Manager regularly collaborates with engineering, data science, and quality assurance teams to align annotation guidelines, project timelines, and quality standards. They often facilitate meetings to clarify requirements, resolve ambiguities in data labeling, and provide feedback on annotation accuracy. This role serves as a bridge between technical teams and annotation staff, ensuring open communication and timely resolution of challenges, which is critical for delivering high-quality datasets essential for machine learning and AI projects.

What are the key skills and qualifications needed to thrive as a data annotation program manager, and why are they important?

To thrive as a Data Annotation Program Manager, you need expertise in project management, data quality assessment, and a solid understanding of machine learning or data annotation processes, typically supported by a relevant degree. Familiarity with annotation platforms, workflow management tools, and data labeling software is essential, along with knowledge of quality assurance frameworks. Strong leadership, problem-solving abilities, and effective communication are crucial soft skills that help manage diverse teams and ensure stakeholder alignment. These skills are important to maintain high data quality, meet project deadlines, and drive successful AI model training initiatives.

What are popular job titles related to Data Annotation Program Manager jobs in California?

For Data Annotation Program Manager jobs in California, the most frequently searched job titles are:

What job categories do people searching Data Annotation Program Manager jobs in California look for?

The top searched job categories for Data Annotation Program Manager jobs in California are:

What cities in California are hiring for Data Annotation Program Manager jobs?

Cities in California with the most Data Annotation Program Manager job openings:

Infographic showing various Data Annotation Program Manager job openings in California as of August 2026, with employment types broken down into 36% Part Time, and 64% Contract. Highlights an 46% In-person, and 54% Remote job distribution.

Product Data Operations Program Manager

Meta

Menlo Park, CA • On-site

$103K - $155K/yr

Full-time

Re-posted 13 hours ago


Meta rating

7.8

Company rating: 7.8 out of 10

Based on 45 frontline employees who took The Breakroom Quiz

139th of 247 rated software companies


Job description

Meta is seeking a Product Data Operations Program Manager to drive AI solutions and data programs that power intelligent products across Meta's portfolio. In this role, you will manage end-to-end data operations programs that support AI model development, training data pipelines, and data quality initiatives - enabling teams to build and ship AI-driven features at scale. You will partner with data science, engineering, product, and operations teams to define program strategies, resolve data pipeline dependencies, and ensure high-quality data outputs that directly influence AI product outcomes.
Responsibilities
Manage and deliver data operations programs that support AI model training, evaluation, and deployment pipelines across product teams
• Partner with data science, engineering, and product teams to define data requirements, prioritize data collection efforts, and align on quality standards for AI solutions
• Identify and resolve bottlenecks in data labeling, annotation, and curation workflows to ensure timely delivery of high-quality training datasets
• Analyze complex data operations challenges and propose scalable solutions that align with AI product roadmaps and organizational goals
• Develop and maintain program documentation, including data governance frameworks, workflow specifications, and milestone tracking for AI data initiatives
• Engage team leaders and cross-functional stakeholders to build alignment on program direction, surface risks early, and drive decisions that unblock data operations work
• Leverage AI tools and workflow automation to improve the efficiency and quality of data operations processes, sharing learnings to scale adoption across the team
• Track and communicate program health metrics - including data throughput, quality rates, and delivery timelines - to stakeholders at varying leadership levels
• Provide input into team-level goals by synthesizing insights from data operations performance and translating them into actionable recommendations for AI product teams
• Adapt program plans in response to shifting AI product priorities, regulatory requirements, or data availability constraints, maintaining focus on highest-impact deliverables
Minimum Qualifications
• 2+ years of experience in program management, data operations, or technical operations roles supporting AI, machine learning, or data-driven product development
• Experience managing cross-functional programs involving data pipelines, data labeling, annotation workflows, or AI training data quality initiatives
• Experience analyzing operational data and communicating findings and recommendations to technical and non-technical stakeholders
• Experience building and maintaining program tracking systems, documentation, and reporting frameworks for complex, multi-team initiatives
• Experience identifying process inefficiencies and implementing scalable solutions within data or AI operations environments
Preferred Qualifications
• Familiarity with data governance practices, metadata management, or compliance considerations relevant to AI training data
• Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
• Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
• Experience working directly with data science or machine learning teams to define data requirements and evaluate dataset quality for AI model development
• Experience managing vendor or outsourced data annotation and labeling operations at scale
• Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
• Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
• Experience using AI-powered tools or workflow automation platforms to redesign and accelerate data operations processes
• Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
• Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
About Meta
Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today-beyond the constraints of screens, the limits of distance, and even the rules of physics.
Equal Employment Opportunity
Meta is proud to be an Equal Employment Opportunity employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or other applicable legally protected characteristics. You may view our Equal Employment Opportunity notice here.

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