Data Annotator (AI)

Location: Hybrid — Washington, D.C., United States

Salary: $42,000–$62,500 annually, based on experience, skills, and qualifications.

Company

hirify.global is a global data engineering company providing data, evaluation frameworks, platforms, and human expertise for generative AI and other AI systems.

What you will do

• Label static imagery and video across real-world and synthetic datasets, sensor types, image qualities, and scene conditions.
• Create 2D bounding boxes, instance and semantic segmentation masks, keypoints, oriented boxes, and rotated boxes according to project specifications.
• Produce 3D annotations, six-degrees-of-freedom pose, orientation, and scale annotations when required.
• Maintain consistent object identities across video sequences, including occlusion, frame exit and re-entry, scale changes, and camera or platform motion.
• Review, correct, and accept or reject model-assisted pre-labels; report systematic failure modes and document edge cases.
• Meet accuracy and throughput targets, complete QA rework, and follow customer data-handling, confidentiality, and information-security requirements.

Requirements

• At least one year of image or video annotation experience, or equivalent precision work in a quality-managed production environment.
• Working familiarity with a professional annotation platform such as CVAT, V7 Darwin, Labelbox, Scale, or a comparable tool.
• Practical understanding of bounding boxes, segmentation masks, keypoints, and object tracking.
• Strong visual attention to detail and the ability to maintain consistent quality across large batches.
• Ability to follow written labeling guidelines exactly and raise precise questions about ambiguous cases.
• Comfort working in remote-desktop or browser-based environments.

Nice to have

• Experience with multiple annotation modalities, long-form video, or tracking workflows.
• Experience with aerial, overhead, satellite, or thermal/IR imagery.
• Experience reviewing model-assisted pre-labels in a human-in-the-loop pipeline.
• Prior work on government or regulated-industry programs.

Culture & Benefits

• Assignments rotate across projects, modalities, and customers according to program needs.
• Work follows defined ontologies, labeling specifications, quality targets, and throughput targets.
• Required project training must remain current.
• Some programs require eligibility for a government background investigation or credentialing.