OverviewDraftAid is building the intelligence layer for mechanical engineering. We started by auto-generating manufacturing drawings from 3D CAD parts. We are now building representations that enable us to go much further.What you'll doDesign learned representations over a large corpus of 3D assemblies and their associated manufacturing drawingsTrain and evaluate models that drive drawing generation decisionsBuild the data and training infrastructure from scratch: pipelines, eval harnesses, dataset curationIntegrate models into a production geometry engine written in C#Own the full ML stack. There is no existing ML team; you are itOwn problems,



not ticketsWhat we're looking forDeep experience training encoder‑decoder architectures and representation learning systems from scratchPractical experience building with LLMs as components in larger systemsComfort working with 3D data: meshes, B‑rep, point clouds, or similar geometric representationsThe ability to look at a messy, domain‑specific corpus and figure out what signal is in itNice to haveExperience with 3D world models and spatial reasoning systemsBackground in robotics perception, 3D reconstruction, NeRFs, or geometric deep learningFamiliarity with C# or TypeScriptWhat we offerFlexible hours and hybrid in-officeCompetitive salary and equity packageSmall team, high ownership#J-18808-Ljbffr

📌 Founding Ml Engineer (Toronto)
🏢 Draftaid
📍 Toronto