Source description
About the role
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
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Design learned representations over a large corpus of 3D assemblies and their associated manufacturing drawings
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Train and evaluate models that drive drawing generation decisions
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Build the data and training infrastructure from scratch: pipelines, eval harnesses, dataset curation
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Integrate models into a production geometry engine written in C#
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Own the full ML stack. There is no existing ML team; you are it
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Own problems, not tickets
What we're looking for
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Deep experience training encoder-decoder architectures and representation learning systems from scratch
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Practical experience building with LLMs as components in larger systems
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Comfort working with 3D data: meshes, B-rep, point clouds, or similar geometric representations
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The ability to look at a messy, domain-specific corpus and figure out what signal is in it
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Nice to have
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Experience with 3D world models and spatial reasoning systems
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Background in robotics perception, 3D reconstruction, NeRFs, or geometric deep learning
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Familiarity with C# or TypeScript
What we offer
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Flexible hours and hybrid in-office
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Competitive salary and equity package.
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Small team, high ownership
More at Draftaid
