Job Description:

• Label construction drawings with bounding boxes, polygons, and segmentation masks to meet accuracy standards
• Apply guidelines consistently across drawings
• Flag ambiguous and edge cases and help improve guidelines
• Clean existing datasets by fixing inconsistent labels, missing metadata, and duplicates
• Meet weekly quality and throughput targets
• Communicate data observations to ML engineers so they can fix model failures faster

Requirements:

• Ability to catch errors, inconsistencies, and missing information
• Ability to follow written instructions precisely and use good judgment when guidelines are incomplete
• Ability to perform focused, repetitive work for hours without losing accuracy
• Ability to learn new tools quickly and work independently remotely
• Clear written English for flagging issues and asking questions
• Remote in the US
• Availability during core Pacific Time hours
• Prior image annotation work in Labelbox, CVAT, or Supervisely (nice to have)
• Basic computer vision concepts, including object detection and segmentation (nice to have)
• Ability to read construction, CAD, or architectural drawings (nice to have)

Benefits:

• Performance bonus
• Equity
• Path to full-time for strong performers
• Remote work
• Contract duration of 3–6 months, 40 hours a week

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