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$43.5K

$127.5K

$239K

How much do director image annotation jobs pay per year?

As of Aug 28, 2026, the average yearly pay for director image annotation in the United States is $127,543.00, according to ZipRecruiter salary data. Most workers in this role earn between $88,000.00 and $150,500.00 per year, depending on experience, location, and employer.

What is a director of image annotation?

A Director of Image Annotation is a senior professional responsible for overseeing the processes involved in labeling and tagging images for use in machine learning and artificial intelligence applications. They manage teams of annotators, develop strategies for efficient and accurate data labeling, and ensure that the annotated data meets the quality standards required for training AI models. This role often involves collaborating with engineers, data scientists, and project managers, as well as implementing best practices and tools to streamline image annotation workflows.

What are the key skills and qualifications needed to thrive as a director of image annotation, and why are they important?

To thrive as a Director of Image Annotation, you need expertise in machine learning, computer vision, data management, and a background in related fields such as computer science or engineering, often complemented by advanced degrees. Familiarity with annotation platforms, quality assurance tools, and project management systems is typically required, along with experience in leading large annotation teams. Strong leadership, communication, and problem-solving skills help drive team performance and ensure clear alignment with project goals. These competencies are crucial for delivering high-quality annotated datasets that power accurate AI models and support organizational objectives.

What are some common challenges faced by a director of image annotation, and how can they be addressed?

A Director of Image Annotation often encounters challenges such as ensuring data quality at scale, managing diverse annotation teams, and keeping up with evolving project requirements. Overcoming these obstacles typically involves implementing robust quality control processes, fostering clear communication between annotators and project stakeholders, and investing in training to keep the team updated on the latest annotation tools and standards. Additionally, balancing deadlines while maintaining high accuracy is crucial, so strong leadership and process optimization skills are essential.

What is the difference between Director Image Annotation vs Data Labeling Specialist?

AspectDirector Image AnnotationData Labeling Specialist
CredentialsExperience in AI, machine learning, or data management; often requires leadership skillsBasic to advanced knowledge of data labeling tools; certifications vary
Work EnvironmentManagement of teams, project oversight, strategic planningHands-on annotation work, using labeling platforms, focused on task execution
Employer & IndustryTech companies, AI firms, research institutionsAI, autonomous vehicles, healthcare, retail sectors
Search & Comparison IntentUnderstanding leadership roles in image annotationLearning about hands-on data labeling tasks

The main difference is that a Director Image Annotation oversees teams and manages projects, focusing on strategy and quality control, while a Data Labeling Specialist performs the actual annotation work, focusing on task execution. Both roles are essential in AI data pipelines but differ in responsibilities and experience levels.

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What cities are hiring for Director Image Annotation jobs?

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Director Image Annotation jobs near you
Infographic showing various Director Image Annotation job openings in the United States as of August 2026, with employment types broken down into 2% As Needed, 83% Full Time, 12% Part Time, 1% Temporary, and 2% Contract. Highlights an 91% Physical, 3% Hybrid, and 6% Remote job distribution, with an average salary of $127,543 per year, or $61.3 per hour.

Data Annotator / Geospatial Annotation Specialist

Aechelon Technology

South San Francisco, CA

$82K - $92K/yr

Full-time

Medical, Dental, Vision, Life, Retirement

Re-posted 8 days ago

Job description

The Data Annotator / Geospatial Annotation Specialist plays a critical role in the creation of high-quality training datasets used to develop and refine Aechelon's machine learning and computer vision models. This role supports both the Advanced Model Development Group and the Applied Real-Time Vision Group, ensuring datasets for object detection, segmentation, and classification are accurate, consistent, and production-ready.
The Specialist performs detailed vector annotation, image segmentation, and dataset preparation while adhering to strict quality standards. Because model performance is highly dependent on high-quality annotation, this role requires exceptional attention to detail and a strong understanding of geospatial imagery.
In addition to dataset creation, the Specialist will learn core machine learning concepts and gain experience operating inference tools and models within the DAML pipeline, becoming a direct contributor to model evaluation and workflow improvements.

Key Responsibilities
  • Create precise vector annotations and segmentation masks for training computer vision and object detection models.
  • Perform detailed image segmentation, manually labeling features across large and varied imagery datasets.
  • Follow established annotation guidelines and maintain consistency across global AOIs.
  • Validate and refine automated detection outputs; correct errors or incomplete detections.
  • Work with ML team to understand annotation needs, edge cases, and quality thresholds.
  • Learn how to operate model inference tools and assist in evaluating model performance.
  • Provide feedback on false positives/negatives, detection weaknesses, and annotation ambiguities.
  • Maintain structured documentation of annotation processes, datasets, feature definitions, and QA results.
  • Support improvements to dataset pipelines and annotation workflows through iterative refinement and testing.
  • Assist multiple DAML groups as needed, depending on dataset demands and model development cycles.
Required Qualifications
  • Background in GIS, Remote Sensing, Image Analysis, Digital Art, Photography, or related field (degree preferred but not required with strong experience).
  • Prior experience with image annotation, data labeling, GIS feature extraction, or segmentation workflows.
  • Ability to visually identify subtle features in imagery with extreme precision.
  • Strong analytical, organizational, and documentation skills.
  • Ability to work with large datasets for extended periods while maintaining accuracy and focus.
Required Skills and Tools
  • Adobe Photoshop (Advanced): Expertise in mask creation, polygon tracing, color differentiation, clean-up workflows, and segmentation editing.
  • GIS Tools (Intermediate+): Ability to work in QGIS, ERDAS Imagine, or Global Mapper for spatial visualization and annotation support.
  • Geospatial Data Handling: Ability to work with shapefiles, GeoPackages, raster datasets, and other formats used in ML workflows.
  • Python (Basic-Intermediate): Ability to run scripts, perform data checks, and assist with pre-processing tasks.
  • Documentation Tools: Proficiency using Jupyter Notebook and Git for tracking annotation notes and revisions.
Strongly Desired Skills and Tools
  • Experience creating training datasets for machine learning, object detection, or image segmentation models.
  • Familiarity with YOLO, PyTorch, or fast.ai (conceptual knowledge acceptable).
  • Ability to create simple scripts to automate annotation steps or pre-processing tasks.
  • Experience using ChatGPT or other LLMs to improve workflows, generate helper scripts, or automate documentation.
  • Understanding of geospatial features such as vegetation, buildings, vehicles, aircraft, or other runtime elements.
Reporting Expectations

The Specialist reports jointly to managers in the Advanced Model Development and Applied Real-Time Vision groups depending on project assignment. Regular updates are expected on dataset progress, annotation quality, workflow blockers, and model evaluation findings. The Specialist is expected to meet annotation quotas while maintaining strict accuracy and quality standards.

Compensation

$82,000 - 92,000 / year 

The above range is specific to CALIFORNIA and may not be applicable to other locations. Final compensation is based on factors such as the candidate's skills, qualifications, and experience. 

 We offer a very attractive compensation package including competitive base salary, company performance-based profit sharing, 401k, 100% employer paid health benefits (medical, dental, vision, life, std, ltd, and life insurance plans). 

No relocation reimbursement provided. 

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