[Hiring] Data Annotation Specialist @Bobyard

Role Description

You’ll label the construction drawings our computer vision models learn from, and work directly with the ML engineers who use your data. We’re adding new trades, so our models need more labeled drawings than ever. The work is repetitive and exacting, and the guidelines won’t cover every case. Success is labels so consistent that engineers use them without a second look.

• Label construction drawings with bounding boxes, polygons, and segmentation masks that meet our accuracy bar
• Apply guidelines consistently, so labels match from the first drawing to the last
• Flag ambiguous and edge cases early, and turn them into sharper guidelines
• Clean existing datasets: fix inconsistent labels, missing metadata, and duplicates
• Hit weekly quality and throughput targets
• Tell ML engineers what you see in the data, so they fix failures faster

Qualifications

• You catch what’s wrong, inconsistent, or missing before anyone points it out
• You follow written instructions precisely, and use good judgment when they run out
• You can do focused, repetitive work for hours without your accuracy slipping
• You learn new tools fast and work well on your own, remotely
• Clear written English for flagging issues and asking questions

Requirements

• Prior image annotation work in Labelbox, CVAT, or Supervisely (nice to have)
• Basic computer vision concepts: object detection, segmentation (nice to have)
• You can read construction, CAD, or architectural drawings (nice to have)

Benefits

• Cash for stability. Bonus for performance. Equity for ownership.
• Your package reflects your role, your experience, and what you deliver, and it grows as you do.
• 20–35/hour + performance bonus
• A path to full-time for strong performers
• Contract, 3–6 months, 40 hours a week. Remote in the US, available during core Pacific Time hours.