Data Annotation Specialist - Computer Vision

Bobyard; San Francisco (CA); Remote; USD 28,000 - 48,000; Full time

Benefits offered by this job

Performance bonus

Remote in the US

Job summary

Bobyard is hiring for a remote labeling role to annotate construction drawings for CV/ML models. You will create bounding boxes, polygons, and segmentation masks, ensuring consistency across the dataset and improving model learning through precise labels.

The work is contract-based (3–6 months) with 40 hours per week, remote within the United States, and Pacific Time availability. You’ll work closely with ML engineers, following strict guidelines, flagging edge cases, and helping shape labeling

Qualifications

• Attention to detail and accuracy
• Follow instructions precisely
• Sustain focused, repetitive work without errors
• Clear written English for flagging issues

Responsibilities

• Label construction drawings with bounding boxes, polygons, and segmentation masks
• Apply guidelines consistently across drawings
• Flag ambiguous cases early and refine guidelines
• Clean existing datasets: fix inconsistent labels, metadata, duplicates
• Meet weekly quality and throughput targets
• Communicate findings to ML engineers to accelerate fixes

Job description

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.