Position Overview
Join the team building computer vision applications for the construction trades.
Contractors spend dozens of hours per project doing takeoffs by hand. We're automating that with models that need to perform reliably on messy, real-world drawings.
As a CV/ML Engineering Intern, you'll work on real production problems alongside our ML team, not a side project. You'll own a scoped piece of work end-to-end, get hands-on mentorship from experienced engineers, and see your models reach customers who use them daily.
Responsibilities
Build and improve CV models for detection, segmentation, or OCR on construction drawings, with guidance from a mentor on the ML team
Contribute to our pipelines: data preparation, labeling workflows, training runs, and evaluation
Run experiments, measure results, and clearly communicate what worked and what didn't
Dig into real customer data to find failure modes and propose fixes
Work with fullstack and product engineers to help get your work into production
Read relevant research and test ideas that could improve our models
Desired Attributes
Currently pursuing a BS, MS, or PhD in Computer Science, Electrical Engineering, or a related field
Solid foundation in deep learning and computer vision through coursework, research, or projects
Hands-on experience training models in PyTorch (or similar), whether in class, research, a prior internship, or personal projects
Strong Python skills
Curiosity about messy, real-world data: scanned, handwritten, imperfect
High ownership: you ask good questions, then run with the answers
Bonus: experience with document AI, OCR, or vision-language models
Details
12-16 weeks, full-time, in person in the SF Bay Area
Paid internship: $55/hr
Strong interns may be considered for full-time roles
We value learning speed and follow-through. If you want to build models that customers trust with high-stakes decisions, we'd love to talk.
Comp Philosophy
Cash for stability. Bonus for performance. Equity for ownership. Your package reflects your role, your experience, and what you deliver.