- Salary
- $140k – $200k/yr
- Location
- Toronto, Ontario, CA
- Workplace
- Hybrid, Onsite
- Type
- Full-time
- Department
- Engineering
- Source
- Y Combinator
Description
- DraftAid is building the intelligence layer for mechanical engineering. We started by auto-generating manufacturing drawings from 3D CAD parts, and we're building the representations to go much further.
What you'll do
- Design learned representations over a large corpus of 3D assemblies and their associated manufacturing drawings
- Train and evaluate models that drive drawing generation decisions
- Build the data and training infrastructure from scratch: pipelines, eval harnesses, dataset curation
- Integrate models into a production geometry engine written in C#
- Own the full ML stack. There is no existing ML team; you are it
- Own problems, not tickets
What we're looking for
- Deep experience training encoder-decoder architectures and representation learning systems from scratch
- Practical experience building with LLMs as components in larger systems
- Comfort working with 3D data: meshes, B-rep, point clouds, or similar geometric representations
- The ability to look at a messy, domain-specific corpus and figure out what signal is in it
Nice to have
- Experience with 3D world models and spatial reasoning systems
- Background in robotics perception, 3D reconstruction, NeRFs, or geometric deep learning
- Familiarity with C# or TypeScript
What we offer
- Flexible hours and hybrid in-office
- Competitive salary and equity package.
- Small team, high ownership
Skills
TypeScriptDeep Learning
