Data Annotation Specialist - Computer Vision
This is the employer's own posting, not a copy on a job board.
What we know
Is it still open?
Confirmed still open
Last checked 1d ago — checked against the employer's own applicant tracking system, which is the company answering directly.
We re-read the employer's own applicant tracking system and the posting was still there. That is the company answering directly.
How old is it?
Posted 1d ago
The date the source published, not the day we noticed it (2026-10-09). Last seen at its source just now.
We have tracked this listing since 9 Oct 2026 (1 days). The employer's own board has carried it every time we have read it, most recently just now.
Is it remote?
Remote
That is the location the employer filed this posting under. Quoted as written — we do not re-word the source's own location.
Who may apply?
Not stated
The description states no restriction of its own. This is the source's own tag.
Skills named in the ad
Recognised terms only, from a fixed vocabulary — this is what CV matching compares against.
Carried by 1 source
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Ashby employer's own board first seen 1d ago · last seen just now
The listing
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.