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Data Annotation Project Manager Jobs in Washington, DC

H5 Data Centers

Data Center Project Manager

Ashburn, VA · On-site

$125K - $130K/yr

Provide Management status of all active Data Center projects and Key Performance indicators. * Lead internal resources and vendors in the execution of Data Center deployments and builds.

General Motors

Senior AI/ML Engineer

Annapolis, MD · On-site +1

$103K - $142K/yr

We partner closely across AI/ML engineers , Product Operations , Product Management , Data Science ... Own projects end‑to‑end Take ownership of technical projects from problem framing through ...

CBRE

Project Manager - Data Center

Ashburn, VA · On-site

$123K/yr

PROJECT MANAGER About the Job: The Project Manager (PM) will be a lead member in our operations ... data centers, or structured cabling environment. • Track record of delivering mission critical ...

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All JobsData Annotation Project JobsData Annotation Project Manager JobsData Annotation Project Manager Jobs in Washington, DC

Data Annotation Project Manager information

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$19

$65

$90

How much do data annotation project manager jobs pay per hour?

As of Jun 8, 2026, the average hourly pay for data annotation project manager in Washington, DC is $65.13, according to ZipRecruiter salary data. Most workers in this role earn between $56.35 and $76.25 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Data Annotation Project Manager, and why are they important?

To thrive as a Data Annotation Project Manager, you need strong project management skills, a solid understanding of data annotation processes, and experience with quality assurance, often supported by a degree in a relevant field. Familiarity with annotation tools (like Labelbox or Supervisely), workflow management platforms, and sometimes agile or PMP certification is highly beneficial. Exceptional communication, attention to detail, and leadership abilities help you effectively coordinate teams and ensure project deliverables meet quality standards. These skills are essential for managing complex annotation projects efficiently, maintaining data integrity, and supporting successful machine learning outcomes.

What are some common challenges faced by Data Annotation Project Managers, and how can they be managed effectively?

One of the primary challenges Data Annotation Project Managers face is ensuring high-quality, consistent labeling across large and sometimes distributed annotation teams. Managing tight deadlines while maintaining annotation accuracy requires effective training, clear guidelines, and regular quality checks. Additionally, balancing communication between data scientists, clients, and annotators is crucial to align expectations and resolve ambiguities quickly. Successful managers often implement robust feedback loops, leverage annotation tools with built-in quality control features, and foster an open environment for continuous improvement.

What is the difference between Data Annotation Project Manager vs Data Labeling Specialist?

AspectData Annotation Project ManagerData Labeling Specialist
CredentialsTypically requires project management experience, certifications in data management or related fieldsOften requires basic technical skills, familiarity with labeling tools, sometimes certifications in data annotation
Work EnvironmentOversees teams, manages projects, coordinates workflows in office or remote settingsPerforms labeling tasks, often in a remote or on-site environment, focused on data tagging
Employer & Industry UsageUsed by tech companies, AI firms, and data service providers for managing annotation projectsEmployed within similar industries, focusing on executing labeling tasks under supervision

The main difference is that the Data Annotation Project Manager oversees and coordinates annotation projects, ensuring quality and deadlines, while the Data Labeling Specialist focuses on executing the labeling tasks themselves. Both roles are essential in the data annotation process but differ in responsibilities and scope.

What is a Data Annotation Project Manager?

A Data Annotation Project Manager is responsible for overseeing projects that involve labeling and categorizing data, such as images, text, or audio, to train machine learning models. They coordinate teams of annotators, manage project timelines, and ensure the quality and accuracy of the annotated data. This role often acts as a bridge between data scientists, clients, and annotation teams, ensuring project requirements are met efficiently and effectively.
What are popular job titles related to Data Annotation Project Manager jobs in Washington, DC? For Data Annotation Project Manager jobs in Washington, DC, the most frequently searched job titles are:
What job categories do people searching Data Annotation Project Manager jobs in Washington, DC look for? The top searched job categories for Data Annotation Project Manager jobs in Washington, DC are:
Data Annotation Project Manager jobs near you

Senior Imagery Analyst (Data Annotation)

Vantor

Falls Church, VA • On-site

$91K - $115K/yr

Full-time

Posted 24 days ago

Job description

Job Summary:
Vantor is forging the new frontier of spatial intelligence, helping decision makers and operators navigate what’s happening now and shape what’s coming next. They are seeking a detail-oriented Senior Imagery Analyst (Data Annotation) to guide and improve annotation workflows across EO, SAR, and commercial imagery while performing quality validation efforts and mentoring junior team members.
Responsibilities:
• Provide quality assurance reviews of annotated geospatial imagery
• Train and mentor junior annotators on best practices
• Identify systemic annotation issues and drive corrective actions
• Validate annotation accuracy across multiple formats (bounding boxes, segmentation, center points)
• Collaborate with peers, quality lead, program managers, and other critical partners to align data output with downstream model needs
• Recommend and implement improvements to annotation tools and processes
• Write and maintain annotation guidelines and quality control documentation
Qualifications:
Required:
• U.S. citizenship and active TS/SCI clearance
• 7+ years of experience with EO, SAR, COMINT, and/or commercial imagery analysis and geospatial data annotation
• Proficiency in geospatial software tools (e.g., ArcGIS, QGIS)
• Experience using Remote View, SOCET GXP, and/or Fade/Mist
• Demonstrated leadership in data validation or quality assurance processes
• Experience with object classification, visual QA, and annotation feedback cycles
Preferred:
• Experience supporting government or defense missions
• Familiarity with automated quality metrics or annotation pipelines
• Experience with SAR-specific feature analysis
• Basic scripting or automation (e.g., Python, Jupyter) is a plus
• Prior experience writing SOPs or developing team workflows
Company:
A spatial intelligence firm. Founded in 2025, the company is headquartered in Denver, USA, with a team of 1001-5000 employees. The company is currently Late Stage.

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