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Annotation Product Manager Jobs (NOW HIRING)

Apptronik

Staff Product Manager, Applied AI

Sunnyvale, CA · On-site

$215K - $245K/yr

Experience with data collection operation (teleoperation fleets, annotation and curation pipelines ... At least 10 years of experience in product management or engineering, including 5+ years leading ...

Marsh McLennan

Applied AI Product Manager

Austin, TX · On-site

Marsh is seeking an Applied AI Product Manager to help translate advances in AI into useful ... Experience with observability, quality dashboards, annotation workflows, or human-in-the-loop ...

Dialpad

Lead Product Manager

San Ramon, CA · On-site

Products like our voice agents and agentic runtime are joint efforts with product engineering ... Where data investment goes: acquisition, annotation, and labeling priorities. * The quality bar ...

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Annotation Product Manager information

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$51.5K

$159.4K

$197K

How much do annotation product manager jobs pay per year?

As of Sep 11, 2026, the average yearly pay for annotation product manager in the United States is $159,405.00, according to ZipRecruiter salary data. Most workers in this role earn between $141,000.00 and $197,000.00 per year, depending on experience, location, and employer.

What is an annotation product manager?

Annotation Product Managers are professionals responsible for overseeing the development, quality, and delivery of data annotation products or services. They work at the intersection of machine learning, product management, and data operations, ensuring that annotated datasets meet the needs of AI and ML teams. Their work involves coordinating with data scientists, annotators, and engineers to define requirements, manage workflows, and ensure high-quality labeled data for training algorithms. Annotation Product Managers play a key role in enabling reliable AI models by ensuring the accuracy and scalability of annotation processes.

What are the key skills and qualifications needed to thrive as an annotation product manager?

To thrive as an Annotation Product Manager, you need a solid understanding of data annotation workflows, product management principles, and experience in AI/ML projects, typically supported by a relevant degree. Familiarity with annotation tools (like Labelbox or Scale AI), agile project management software, and possibly certifications such as PMP or Scrum are highly valuable. Strong communication, stakeholder management, and problem-solving abilities help you collaborate across technical and non-technical teams. These skills are crucial to deliver high-quality labeled data, align cross-functional objectives, and ensure the success of AI-driven products.

How does an annotation product manager typically collaborate with engineering and data science teams?

Annotation Product Managers work closely with engineering and data science teams to define product requirements, prioritize annotation features, and ensure high-quality labeled data is delivered for machine learning projects. They often facilitate cross-functional meetings, translate business needs into technical specifications, and help resolve any blockers related to data annotation processes. Effective communication and a clear understanding of the annotation workflow are essential, as these teams rely on the Product Manager to align objectives and keep projects on schedule.

What is the difference between Annotation Product Manager vs Data Scientist?

AspectAnnotation Product ManagerData Scientist
Required CredentialsBachelor's in CS, Business, or related; experience in product managementBachelor's or higher in CS, Statistics, or related; advanced analytics skills
Work EnvironmentCollaborates with engineering, data teams, and stakeholders on annotation tools and processesAnalyzes data, builds models, and interprets complex datasets
Industry UsageUsed in AI, machine learning, and data labeling projectsApplied across tech, finance, healthcare for data analysis and modeling

The Annotation Product Manager focuses on managing annotation tools and workflows to support AI projects, while the Data Scientist analyzes data and develops models. Both roles require technical knowledge, but differ in their primary responsibilities and focus areas within data projects.

What are popular job titles related to Annotation Product Manager jobs?

For Annotation Product Manager jobs, the most frequently searched job titles are:

Infographic showing various Annotation Product Manager job openings in the United States as of September 2026, with employment types broken down into 86% Full Time, 13% Part Time, and 1% Contract. Highlights an 86% Physical, 2% Hybrid, and 12% Remote job distribution, with an average salary of $159,405 per year, or $76.6 per hour.

Product Manager, Evals & Improvement

Menlo Park, CA

Meta
Internet and IT • 10K+ employees
Learn more about Metaexternal

$146K/yr

Full-time

Posted 23 days ago

Key responsibilities

  • Own the end-to-end feedback and improvement system, including collection, analysis, prioritization, and resolution.

  • Define how to measure agent quality across dimensions such as accuracy, helpfulness, reliability, and safety.

  • Partner with ML and data science teams to turn feedback into model improvements, eval frameworks, and training data.

Meta rating

7.8

Company rating: 7.8 out of 10

Based on 45 frontline employees who took The Breakroom Quiz

Job description

The Agent Transformation Accelerator (ATA) Product team is building Meta’s future of work: Metamate, an internal full-stack platform that lets people direct, review, and help agents improve their work across the entire company. We’re building the platform components, memory systems, improvement loops, and shared product experiences that make agentic AI genuinely useful for product development. This role owns how we measure and raise the quality of agentic systems (multi-step trajectories, tool use, and partial credit).This is an early-stage, high-leverage role that contributes directly to Metamate's topline revenue, growth, and velocity. You'll shape the approach from the ground up in a space where the right metrics don't yet exist, defining what "good" means for agents and owning the eval verdict that gates model upgrades, harness changes, and major launches. Expect to be constantly learning, working shoulder-to-shoulder with engineering, data science, and ML, including our partners across ATA and Meta Superintelligence Labs (MSL), to turn signal from real usage into a continuous improvement loop that makes the product measurably better every week.
Product Manager, Evals & Improvement Responsibilities:
  • Own the end-to-end feedback and improvement system: collection, analysis, prioritization, and resolution.
  • Define how we measure agent quality across dimensions (accuracy, helpfulness, reliability, safety).
  • Build product mechanisms that capture implicit and explicit user signal at scale.
  • Partner with ML and data science to turn feedback into model improvements, eval frameworks, and training data.
  • Drive the evals and measurement strategy: what "good" looks like, how we detect regressions, and how we track progress.
  • Create transparency and accountability for quality across the ATA Product team.

Minimum Qualifications:
  • Strong quantitative skills and experience defining complex metrics
  • Comfort with ambiguous problem spaces where the right metrics do not yet exist
  • 5+ years of relevant industry experience with at least 2 years in Product Management
  • Bachelor's degree (or relevant degree equivalent): STEM subject ideal but not essential (Computer Science, Engineering, Information Systems, Analytics, Mathematics, Physics, Applied Sciences)
  • Experience partnering closely with data science and ML engineering teams
  • Track record of driving product improvements through data and experimentation
  • Direct experience building evals for AI products end to end: task set construction, rubric design, instrumentation, and analysis
  • Experience running eval-driven development cycles, with a clear view of where evals are informative and where they mislead
  • Willingness to get into the weeds of eval data and rubrics, with high standards for eval rigor and an obsession with quality
  • Deep understanding of LLM capabilities and failure modes

Preferred Qualifications:
  • Experience building annotation, labeling, or crowd-sourcing systems
  • Experience with reinforcement learning from human feedback (RLHF) or similar human-in-the-loop systems
  • Background in evals, trust and safety measurement, or ML quality infrastructure
  • 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

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.
Meta is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Meta participates in the E-Verify program in certain locations, as required by law. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.
Meta is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at accommodations-ext@meta.com.
$146,000/year to $204,000/year + bonus + equity + benefits
Individual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base compensation, Meta offers benefits. Learn more about benefits at Meta.

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