The posting
Aechelon Technology, a Shield AI company, is a leading producer of 3D simulator content, including Geospecific visual/sensor databases and realistic 3D models. We seek people who share our passion for real-time computer graphics and commitment to our mission of helping make our Nation’s pilots safer. We will give you a chance to work with some of the most talented people in the graphics industry.
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.
This position description is not intended to be a complete listing of activities, duties or responsibilities that are required of the employee holding this position. Duties, responsibilities and activities may be changed or others may be assigned at any time by the Company with notice to the employee.
Shield AI is an equal opportunity employer. We are committed to providing access and opportunities to individuals with disabilities. If you are an applicant who is unable to fully utilize/access our application process because of a disability, Aechelon Technology will provide a reasonable accommodation. Please send an email to [email protected] to request that accommodation, and please be sure to include a detailed description of your requested accommodation, your name and preferred method of contact.
