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Annotation Product Manager Jobs (NOW HIRING)

Innodata Inc.

Data & Annotation Engineer

Washington, DC · On-site

$55 - $60/hr

You'll administer the annotation toolchain, manage annotation workflows across the corpus, and ... Phase D corpus production (Weeks 17-19) is the core demonstration deliverable. Candidates must be ...

Innodata Inc.

$55 - $60/hr

You'll administer the annotation toolchain, manage annotation workflows across the corpus, and ... Phase D corpus production (Weeks 17-19) is the core demonstration deliverable. Candidates must be ...

Troveo AI Inc

Senior Product Manager

San Francisco, CA · On-site +1

$140K - $180K/yr

We are looking for a Senior Product Manager to own products and outcomes end to end across this ... annotation, and downstream delivery. * Help design processing pipelines and logic tailored to ...

EvenUp

Product Manager, AI Entities

San Francisco, CA · Remote

$177K - $209K/yr

Drive decisions on model performance, annotation strategy, and integration with continuous inference systems as the underlying ML approaches evolve. What we look for: * 5+ years of product management ...

EvenUp Inc

Product Manager, AI Entities

San Francisco, CA · On-site

$177K - $209K/yr

Drive decisions on model performance, annotation strategy, and integration with continuous inference systems as the underlying ML approaches evolve. What we look for: * 5+ years of product management ...

EvenUp

Product Manager, AI Entities

San Francisco, CA · On-site

Drive decisions on model performance, annotation strategy, and integration with continuous inference systems as the underlying ML approaches evolve. What we look for: * 5+ years of product management ...

EvenUp

Product Manager, AI Entities

San Francisco, CA · Remote

$177K - $209K/yr

Drive decisions on model performance, annotation strategy, and integration with continuous inference systems as the underlying ML approaches evolve. What we look for: * 5+ years of product management ...

Simbe Robotics, Inc.

$120K - $155K/yr

You will improve the quality, speed, and reliability of data used to train and evaluate production ... Experience managing external annotation vendors or distributed annotation teams. $120,000 - $155 ...

Meta

Product Manager, Evals & Improvement

New York, NY · On-site

$146K/yr

Product Manager, Evals & Improvement Responsibilities: * Own the end-to-end feedback and ... Experience building annotation, labeling, or crowd-sourcing systems * Experience with reinforcement ...

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Annotation Product Manager information

See salary details

$51.5K

$159.4K

$197K

How much do annotation product manager jobs pay per year?

As of Sep 10, 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.

Data & Annotation Engineer

Washington, DC • On-site

Innodata Inc.
IT Services • 501 - 1,000 employees
Learn more about Innodata Inc.external

$55 - $60/hr

Full-time

Re-posted 2 days ago

Key responsibilities

  • Administer the annotation toolchain, manage annotation workflows, and produce documentation for governance.

  • Configure and operate the CVAT annotation pipeline during corpus production.

  • Support quality control and associate provenance records with annotated and synthetic outputs.

Innodata rating

7.5

Company rating: 7.5 out of 10

Based on 6 frontline employees who took The Breakroom Quiz

Job description

About the Program: 

Innodata's Federal Practice builds the trusted data layer for critical infrastructure Trust & Safety work. Partnering with a leading systems integrator, we're delivering a modern, governed data services platform in a secure federal (IL4) environment. Over an intensive 20-week phase, you'll help stand up a data services storefront, a DataCard governance framework, synthetic data integration, and Databricks write-back capabilities.

About the Role: 

As the Data/Annotation Engineer, you'll be hands-on with the data itself. You'll administer the annotation toolchain, manage annotation workflows across the corpus, and produce the per-dataset documentation that feeds our governance framework. You'll work with the AI Solutions Engineer to ensure the data going into our models is accurate, well-labeled, and fully traceable. This role is for someone detail-obsessed who understands that great AI starts with disciplined, well-governed data.

Key Responsibilities:

  • Receive, validate, ingest, and ontology-map the ODIN mission-aligned corpus from AFS delivery
  • Produce the ODIN load report: corpus description, ontology mapping, readiness state
  • Configure CVAT annotation pipeline against the Phase 1 starter kit rule pack
  • Operate both self-service and lightweight white-glove annotation paths during Phase D corpus production
  • Produce 50-100 label demonstration corpus across synthetic and mission-aligned content
  • Support QA/Evaluation Lead on QC execution and corpus annotation dry-runs
  • Associate DataCard provenance records with annotated and synthetic outputs in coordination with the Solution Architect

Must-Have Qualifications:

  • Bachelor's degree in Data Science, Computer Science, or related field preferred. Equivalent experience may substitute for degree on a 2-for-1 basis.
  • 5+ years total professional experience, 3+ years in data engineering or annotation operations
  • CVAT - deployment and day-to-day operation required; this is not a nice-to-have
  • Annotated dataset ingest pipelines: schema mapping, format validation, ontology alignment
  • Full-motion video (FMV) annotation concepts and tooling
  • Python scripting for data wrangling, validation, and format conversion
  • Active Secret clearance with TS/SCI eligibility

Nice-to-Have Qualifications:

  • Bachelor's degree in Computer Science, Machine Learning, Data Science, or related field required; Master's degree preferred. Equivalent experience may substitute for degree on a 2-for-1 basis
  • CVAT annotation platform - AI feature configuration and operation
  • DoD or IC data program experience: CUI, distribution statements, federal data governance
  • Evaluation design for AI/ML training data: IAA methodology, drift detection, model performance measurement
  • Video understanding or FMV annotation experience
  • DataCard or ML data provenance framework familiarity

The expected hourly salary range for this position is $55 to $60 p/hour, based on experience, skills, and qualifications.

Note to Candidates: 

Phase D corpus production (Weeks 17-19) is the core demonstration deliverable. Candidates must be genuinely comfortable operating CVAT at production quality against a mission dataset under a milestone deadline

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