Computer Vision Research Engineer - Intern
Quick Summary
data preparation, labeling workflows, training runs, and evaluation Run experiments, measure results,
Responsibilities
~1 min read- →
Build and improve CV models for detection, segmentation, or OCR on construction drawings, with guidance from a mentor on the ML team
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Contribute to our pipelines: data preparation, labeling workflows, training runs, and evaluation
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Run experiments, measure results, and clearly communicate what worked and what didn't
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Dig into real customer data to find failure modes and propose fixes
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Work with fullstack and product engineers to help get your work into production
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Read relevant research and test ideas that could improve our models
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
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.
We are proud to offer competitive, top-of-market compensation because we want to celebrate the dedicated people who ship amazing work and drive our success. Our individual compensation is thoughtfully tailored based on your role, experience, and contributions, alongside performance-based rewards.
Location & Eligibility
Listing Details
- Posted
- October 5, 2026
- First seen
- October 5, 2026
- Last seen
- October 10, 2026
Posting Health
- Days active
- 4
- Repost count
- 0
- Trust Level
- 42%
- Scored at
- October 10, 2026
Signal breakdown
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