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Data Annotation Program Manager Jobs (NOW HIRING)

TEKsystems

Data Annotation Specialist

Seattle, WA · Remote

$20/hr

Use annotation tools to mark up text, images, or other data according to specific guidelines ... Benefits are subject to change and may be subject to specific elections, plan, or program terms. If ...

Q Analysts

Data Annotation Technician

Kirkland, WA · On-site

Q Analysts provides industry-leading managed services that drive Quality for Quality Assurance and ... Program. Learn about us here and come join us. Q Analysts is a high growth technology consulting ...

Q ANALYSTS LLC

Data Annotation Technician

Kirkland, WA · On-site

Q Analysts provides industry-leading managed services that drive Quality for Quality Assurance and ... Program. Learn about us here and come join us. Q Analysts is a high growth technology consulting ...

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$97.1K

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How much do data annotation program manager jobs pay per year?

As of Aug 25, 2026, the average yearly pay for data annotation program manager in the United States is $97,145.00, according to ZipRecruiter salary data. Most workers in this role earn between $66,000.00 and $125,500.00 per year, depending on experience, location, and employer.

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.
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Data Annotation Program Manager jobs near you
Infographic showing various Data Annotation Program Manager job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 78% Full Time, 17% Part Time, and 4% Contract. Highlights an 96% Physical, 1% Hybrid, and 3% Remote job distribution, with an average salary of $97,145 per year, or $46.7 per hour.

Senior Technical Program Manager (AI/ML)

Seattle, WA • On-site

MDAEdge
See more jobs at MDAEdgeexternal

Full-time

Re-posted 23 days ago

Job description

Job Summary:
MDAEdge is seeking a Technical Program Manager to lead data annotation programs for AI research. This role combines program management, data operations, and AI/ML to deliver scalable, high-quality data labeling aligned with research and product needs.
Responsibilities:
• Drive end-to-end data annotation programs, including scoping, delivery, and post-mortem analysis.
• Collaborate with AI research leaders, researchers, data scientists, ML engineers, and product managers to define data needs, metrics, and guidelines.
• Manage vendors and internal teams, handling contracts, SLAs, quality standards, and throughput.
• Design quality control pipelines, annotation tools, and feedback loops for scalable data quality.
• Partner with engineering to enhance annotation infrastructure, workflows, and data pipelines.
• Support data governance, including privacy, security, ethics, and compliance.
• Track metrics like cost, quality, speed, and volume; report progress to stakeholders.
• Coordinate internal adoption of AI products via onboarding, workflows, and change management.
• Standardize processes to measure, monitor, and improve data quality across teams and datasets.
• Engage customers and partners in workshops, pilots, and feedback for continuous improvement.
Qualifications:
Required:
• Bachelor's or Master's in Computer Science, Data Science, Machine Learning, Information Systems, or equivalent experience.
• 7+ years in technical program management, project management, or operations in data/AI/ML environments.
• Strong knowledge of ML workflows, data pipelines, and annotation lifecycles.
• Experience leading large-scale data labeling or collection with third-party vendors.
• Familiarity with big data platforms and data warehousing.
• Advanced SQL skills for analytics, tracking, forecasting, visualization, reports, and dashboards.
• Proven ability to perform root cause analysis on data and processes for business insights.
• Excellent organizational, problem-solving, communication, negotiation, and analytical skills.
• Experience documenting standard operating procedures.
• Ability to influence cross-functional teams and deliver complex projects on time with high quality.
• Self-motivated; thrives independently and in teams.
Preferred:
• Knowledge of GPU technology in generative AI/ML.
• Familiarity with Apache Spark, Delta Lake, MLflow.
Company:
The world doesn't have a talent shortage. It has a talent alignment problem. MDA Edge exists to fix that. Founded in , the company is headquartered in Sheridan, WY, US, , with a team of 51-200 employees. The company is currently Growth Stage.

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