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Data Annotation Manager Jobs in Washington (NOW HIRING)

Vantor

Senior Imagery Analyst (Data Annotation)

Falls Church, VA · On-site

$91K - $115K/yr

... 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 ...

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Data Annotation Manager information

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$35.1K

$110K

$194.8K

How much do data annotation manager jobs pay per year?

As of Jul 11, 2026, the average yearly pay for data annotation manager in Washington is $110,026.00, according to ZipRecruiter salary data. Most workers in this role earn between $74,800.00 and $142,100.00 per year, depending on experience, location, and employer.

What is the salary of data annotation manager?

The salary of a data annotation manager typically ranges from $60,000 to $120,000 annually, depending on experience, location, and company size. Senior roles or those in high-cost areas may offer higher compensation, and familiarity with annotation tools and team management can influence pay levels.

How much do data annotation project managers make?

Data annotation project managers typically earn between $60,000 and $100,000 annually, depending on experience, location, and company size. They oversee annotation teams, coordinate workflows, and ensure quality standards are met, often requiring familiarity with annotation tools and project management skills.

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

Data Annotation Managers often encounter challenges such as maintaining high annotation quality across large and diverse datasets, managing a distributed team of annotators, and meeting tight project deadlines. To address these, it's important to implement robust quality assurance processes, provide ongoing training for annotators, and establish clear communication channels. Leveraging annotation tools with built-in validation features can also help ensure consistency and accuracy. Building a positive and collaborative team environment further contributes to better outcomes and workflow efficiency.

What does a Data Annotation Manager do?

A Data Annotation Manager oversees the process of labeling and categorizing data used to train machine learning models. They manage teams of annotators, ensure data quality, develop annotation guidelines, and coordinate with data scientists to meet project requirements. Their role is critical in maintaining high standards of accuracy and efficiency, as well as ensuring that datasets are properly prepared for AI and machine learning applications.

Does data annotation actually pay well?

Data annotation managers typically earn competitive salaries that reflect their experience and responsibilities, often ranging from entry-level to senior roles. Compensation can vary based on industry, location, and company size, with specialized skills in tools like labeling platforms and quality control often leading to higher pay.

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

To thrive as a Data Annotation Manager, you need expertise in data labeling processes, quality control, and a solid understanding of machine learning concepts, usually backed by a degree in computer science or a related field. Proficiency with annotation tools such as Labelbox, Supervisely, or CVAT, as well as experience with project management systems, is commonly required. Exceptional leadership, attention to detail, and strong communication skills help manage teams and ensure high annotation accuracy. These skills are critical for delivering reliable labeled datasets, which are essential for building effective AI and machine learning models.

How hard is it to get hired by data annotation?

Getting hired as a data annotation manager typically requires relevant experience in data labeling, familiarity with annotation tools, and strong organizational skills. The hiring process often involves reviewing previous work, technical assessments, and demonstrating attention to detail, with opportunities available in companies that outsource data labeling tasks.

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

AspectData Annotation ManagerData Labeling Specialist
CredentialsBachelor's degree in related field, experience in data managementHigh school diploma or equivalent, training in labeling tools
Work EnvironmentTeam management, project oversight, collaboration with data scientistsHands-on labeling work, using annotation tools, focused on data tagging
Industry UsageUsed in AI/ML projects for overseeing annotation teamsPerforms the actual data labeling tasks in machine learning workflows

The Data Annotation Manager oversees the entire annotation process, managing teams and ensuring quality, while the Data Labeling Specialist focuses on executing labeling tasks. Both roles are essential in AI/ML data preparation but differ in responsibilities and scope.

What are the most commonly searched types of Data Annotation jobs in Washington? The most popular types of Data Annotation jobs in Washington are:
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Data Annotation Manager jobs near you

Senior Imagery Analyst (Data Annotation)

Vantor

Falls Church, VA • On-site

$91K - $115K/yr

Full-time

Re-posted 27 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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