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["Video Game Development","Mobile Gaming"]

Data Annotation Specialist - Computer Vision

RemoteRemoteContract$20–$35 /hrPosted 28 days ago

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Required skills

  • labeling
  • computer vision models
  • accuracy bar
  • guidelines
  • ambiguous cases
  • edge cases
  • clean datasets
  • inconsistent labels
  • missing metadata
  • duplicates

Nice to have

  • Labelbox
  • CVAT
  • Supervisely
  • object detection
  • segmentation
  • construction drawings

Role summary

Bobyard is seeking a Data Annotation Specialist for Computer Vision to label construction drawings for their AI models. This role involves applying guidelines consistently, cleaning datasets, and communicating with ML engineers. The ideal candidate is detail-oriented, follows instructions precisely, and can perform repetitive work accurately. Prior annotation experience and basic computer vision concepts are a plus. This is a remote, contract position in the US, working 40 hours/week during Pacific Time hours, with potential for full-time conversion.

About BobyardConstruction is a multi-trillion-dollar industry that still estimates by hand. Contractors measure and count materials off drawings manually, and it caps how many jobs they can bid. Bobyard uses computer vision and NLP to automate takeoffs and estimates, so contractors bid faster and win more. We raised a $35M Series A led by 8VC, with Primary and Pear, and we’re growing fast.

About the role

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.

What you’ll do

  • 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

What we’re looking for

  • 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

Nice to have

  • Prior image annotation work in Labelbox, CVAT, or Supervisely

  • Basic computer vision concepts: object detection, segmentation

  • You can read construction, CAD, or architectural drawings

A note on paceWe move fast, and priorities shift as we learn from customers. Playbooks, context, and requirements are often incomplete when work starts, and you’ll be expected to shape them. If that pace excites you, you’ll fit in well.

What we offer

  • 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.

Comp Philosophy

Cash for stability. Bonus for performance. Equity for ownership. Your package reflects your role, your experience, and what you deliver.

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