Data Annotation Specialist - Computer Vision

Bobyard
San Francisco, CA
RemoteCareer-pivot friendly

Who this role is best for

A natural match if you have experience with image annotation tools and construction domain knowledge.

Best fit for

  • Candidates with prior image annotation experience and the ability to interpret construction drawings independently
    — “Prior image annotation work in Labelbox, CVAT, or Supervisely”
  • Individuals who thrive in dynamic environments with incomplete guidelines and evolving priorities
    — “Playbooks, context, and requirements are often incomplete when work starts”
  • People who can maintain high accuracy during long hours of repetitive, detail-oriented work
    — “You can do focused, repetitive work for hours without your accuracy slipping”

Things to consider

  • Remote work is required, but availability during core Pacific Time hours is necessary for collaboration
    — “Remote in the US, available during core Pacific Time hours”
  • This role demands consistent output with strict weekly quality and throughput targets
    — “Hit weekly quality and throughput targets”

How to stand out

  • Highlight experience with object detection and segmentation in your resume or interview responses
    — “Basic computer vision concepts: object detection, segmentation”
  • Showcase your ability to identify inconsistencies or ambiguities in data labeling
    — “You catch what’s wrong, inconsistent, or missing before anyone points it out”
  • Emphasize your communication skills for clearly documenting issues and feedback
    — “Clear written English for flagging issues and asking questions”
  • Demonstrate your track record of improving annotation guidelines through feedback
    — “Flag ambiguous and edge cases early, and turn them into sharper guidelines”
  • Demonstrate your ability to work independently without constant supervision
    — “You learn new tools fast and work well on your own, remotely”
Pace · Fast PacedCollaboration · LowAutonomy · MediumDecision Impact · Individual

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • label construction drawings
  • apply guidelines consistently
  • flag ambiguous cases
  • clean existing datasets
  • hit quality and throughput targets
Typical background
prior image annotation workbasic computer vision conceptsability to do focused, repetitive work

Skills & requirements

Required

Data LabelingQuality AssuranceData CleaningCommunicationTime Management

Preferred

Image AnnotationComputer Vision ConceptsConstruction DrawingsCAD Drawings

Stack & domain

Computer VisionData AnnotationImage AnnotationLabelboxCvatSuperviselyAttention To DetailConsistencyProblem SolvingTime Management

About the role

Original posting from Bobyard via Ashby

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.

Source: Bobyard careers (Ashby)

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