About Bobyard
Construction is a multi-trillion industry running on PDFs, rulers, and 1990s software. The biggest choke point is the cost estimate. Takeoffs are manual, slow, and one mistake blows millions. We use computer vision and NLP to read drawings like an expert estimator, 10x faster and with fewer mistakes. We're backed by 8VC, Primary, and Pear.
About the role
You'll own a model-powered product surface end to end: not writing specs and handing them off, but being the person engineering and customers both come to when the question is "why did the model do that, and what do we do about it."
What you'll do
Own the roadmap for a model-powered product surface, from customer problem to shipped feature
Read eval reports and confusion matrices well enough to argue with the CV engineers, not just relay their conclusions
Make and defend accuracy/speed/cost tradeoffs — in the room with engineering, and directly with customers
Build and maintain eval sets that keep the team honest about model performance
Decide when a model is actually ready to ship — not based on aggregate accuracy, but on which failure modes are cheap to catch downstream and which are expensive to miss
Turn ambiguous customer complaints ("it missed something") into a specific, testable model or UX fix
Work daily with our CV and ML engineers as a peer who understands the model, not a translator layer
What we're looking for
4+ years in product, with real ownership of a model-powered feature (not just "worked with" a data science team)
Fluent in model evaluation — precision, recall, false positive/negative tradeoffs — and can reason about when "85% accurate" is good enough versus when it isn't, based on the cost of the specific errors, not just the aggregate number
Has shipped 0-to-1 or a major iteration on an ML/CV-driven product in B2B SaaS
Comfortable being the last line of defense on "will this model actually work" for customers and execs
Fast learner — no construction background required, but you'll need to be dangerous in it within 30 days
Ships fast, iterates in public, doesn't hide behind process
Nice to have
Prior experience specifically in computer vision (vs. NLP/LLM-only)
Background at a company like Scale AI, Labelbox, Samsara, Matterport, Cape Analytics, or DroneDeploy
Comfortable in Figma and reading code, even if you don't ship it
What we offer
$160K–$180K base + equity
Full-time, in-person in San Francisco — we build together
Comp Philosophy
Cash for stability. Bonus for performance. Equity for ownership. Your package reflects your role, your experience, and what you deliver.