Data Annotation Specialist - Computer Vision

Bobyard

United StatesRemote onlyContractor
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Pay
$20 to $35
an hour
Location
United States
Work style
Remote only
Job type
Contractor
Posted
Oct 9
11 days ago
Career path

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About the company

Bobyard

Internet · 2 to 10 employees

Construction 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.

Bobyard on LinkedIn

What you'll do

  • Label construction drawings with bounding boxes, polygons, and segmentation masks; apply guidelines and clean existing datasets.
  • Flag ambiguous cases, meet weekly quality and throughput targets, and share data observations with ML engineers.

What you need

  • Must follow written instructions precisely, use good judgment, sustain focused repetitive work without losing accuracy, learn tools quickly, work independently, and communicate clearly in written English.
  • Prior image annotation and familiarity with computer vision or construction drawings are nice to have.

Key skills

LabelboxCVATSuperviselycomputer visionobject detectionsegmentationconstruction drawingsCADarchitectural drawingswritten English

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Perks

  • performance bonus
  • Equity
  • path to full-time

See full description on company page, apply now

Read the full posting here
About Bobyard Construction 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 pace We 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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