Founding ML Engineer

Draftaid
Toronto
Workplace: HybridFull timeCAD 140,000 - 200,000 annuallyFunction: Data Science & Machine LearningSkills: ["Ownership","Problem-solving"]

Founding ML Engineer to own the full ML stack for an AI-driven mechanical engineering platform. You’ll design learned representations over 3D assemblies, train encoder-decoder models from scratch, evaluate models, and build data/training infrastructure, integrating these models into a production geometry engine written in C#. You are the sole ML lead, shaping the system from inception with hybrid in-office collaboration.

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Draftaid
Draftaid
4 months ago

Founding ML Engineer

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Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 16 hours agoStatus: Live

Job Summary

Founding ML Engineer to own the full ML stack for an AI-driven mechanical engineering platform. You’ll design learned representations over 3D assemblies, train encoder-decoder models from scratch, evaluate models, and build data/training infrastructure, integrating these models into a production geometry engine written in C#. You are the sole ML lead, shaping the system from inception with hybrid in-office collaboration.
Location: Toronto
Workplace: Hybrid
Employment Type: Full time
Job Function: Data Science & Machine Learning

Key Responsibilities

  • •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 and drive solutions, not tickets.

Pay and Benefits

Salary: CAD 140,000 - 200,000 annually
Equity and Bonus:Equity
Perks:Equity

Key Requirements

  • •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.
  • •Ability to look at a messy, domain-specific corpus and figure out what signal is in it.
  • •Familiarity with C# or TypeScript is a nice-to-have
Experience:3D dataCADGeometryMachine learningAI
Skills:OwnershipProblem-solving
Tech Stack:PythonPyTorchTensorFlowC#LLMs3D dataMeshesPoint cloudsNeRFsGeometric deep learning

Company Brief

Draftaid
Provides an AI-driven drafting assistant that helps users create, refine, and format written documents quickly using templates, generative suggestions, and collaboration tools to accelerate writing workflows and improve output quality.
Industry: Enterprise Software
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