Overview
DraftAid 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 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

Market-competitive salary and equity package

Small team, high ownership

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📌 Founding ML Engineer (Ontario)
🏢 Draftaid
📍 Ontario