The Role
You’ll turn research ideas into production-grade models that directly shape the product.
What You’ll Do
• Research and prototype ML approaches for automated clash detection in complex engineering drawings (MEP, structural, civil)
• Develop computer vision pipelines for detecting geometric conflicts across layered technical plans
• Design and evaluate models that understand spatial relationships, symbols, and annotations
• Work with large-scale PDF and BIM-derived datasets
• Build data curation, labeling, and evaluation frameworks
• Experiment with multimodal approaches (vision + structured metadata + rules)
• Optimize inference performance for real-world deployment
• Document findings and contribute to our internal research roadmap
What We’re Looking For
• Strong foundations in machine learning (deep learning, optimization, statistics)
• Experience with Python and ML frameworks (PyTorch preferred)
• Familiar with computer vision concepts (detection, segmentation, embeddings, etc.)
• Comfortable reading research papers and implementing ideas from scratch
• Curious, experimental, and willing to challenge assumptions
• Excited about applying ML to physical-world systems (not just benchmarks)
You’ll work directly with founding engineers on problems at the intersection of: computer vision, spatial reasoning, document intelligence, and real-world infrastructure systems.
Why Join
• YC-backed, well-funded, and already generating revenue
• Publish-worthy research problems with real-world impact
• Access to proprietary datasets in a massive, underserved domain
• Learn from Oxford-trained AI researchers
• Vibes: smart, ambitious, funny, no ego, deeply care about great work
Benefits
Awesome
Salary
Awesome
Equity
Awesome
Team
Awesome
Product
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