Data Annotation Specialist - Computer Vision

Bobyard; Menlo Park (CA); Remote; USD 28,000 - 48,000; Full time

Benefits offered by this job

Performance bonus

Equity for ownership

Remote in US

Contract 3–6 months

Path to full-time

Job summary

Bobyard is building AI-powered tools for construction takeoffs. You will label drawings for our ML models, using guidelines to ensure consistency across the dataset and improve model learning.

The role supports remote work in the United States and offers a path to stability through a contract arrangement. You will work with ML engineers, focus on repetitive, precise labeling, and help develop clearer data-generation rules as we scale to new trades.

Qualifications

• 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.

Responsibilities

• 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.

Skills

Attention to detail

Remote work capable

English proficiency

Self-directed

Fast learner

Tools

Labelbox

CVAT

Supervisely

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.