Research Software Engineer: Geometry & AI for CAD/CAE

Foundation Llm Technologies

United States

Remote

USD 140,000 - 200,000

Full time

4 days ago
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Job summary

Foundation Llm Technologies is building an applied AI co-pilot for design and manufacturing, bridging theory and real-world engineering challenges. You will work with 2D/3D CAD/CAE data, develop geometry processing and simulation algorithms, and contribute to data pipelines and ML workflows.

The role emphasizes strong Python and ML skills, with exposure to CAD/CAM/CAE systems and DSL/compiler efforts. Experience across academia or industry with a bridging mindset is valued.

Qualifications

  • Experience with Code Development, Computational Design, or Geometry Processing.
  • Strong Python and ML background; practical engineering knowledge preferred.
  • Experience developing CAD/CAM/CAE software tools and LLMs is a plus.

Responsibilities

  • Design, develop, and maintain geometry processing and simulation algorithms for engineering applications.
  • Build services for reading, processing, and writing 2D/3D engineering data.
  • Develop rendering modules for generating 2D/3D visual assets.
  • Curate and manage large-scale datasets for learning-based systems.
  • Implement and optimize post-training workflows for machine learning models.
  • Contribute to the development of domain-specific languages for engineering tasks.

Skills

Python programming
Machine Learning
Geometric Processing
Simulation
Domain-Specific Languages
Data pipelines

Education

PhD or MS in Computational Design/Simulation/AI

Tools

CAD/CAM/CAE software tools

Job description

Foundation Llm Technologies is building an applied AI co-pilot for design and manufacturing, bridging theory and real-world engineering challenges. You will work with 2D/3D CAD/CAE data, develop geometry processing and simulation algorithms, and contribute to data pipelines and ML workflows.

The role emphasizes strong Python and ML skills, with exposure to CAD/CAM/CAE systems and DSL/compiler efforts. Experience across academia or industry with a bridging mindset is valued.

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