Research & Development Software Engineer- Geometry & AI

Posted 23 Days Ago
Hiring Remotely in Boston, MA, USA
In-Office or Remote
Senior level
Artificial Intelligence • Design • Generative AI • Manufacturing
Engineering General Intelligence
The Role
Design and develop geometry processing algorithms and simulation services for engineering applications, focusing on integrating machine learning with practical engineering tasks.
Summary Generated by Built In
REQUIRED: MUST have experience with Code Development. Applicants will not be considered without this experience.
 
About Us:
 
We are an MIT-born, venture-backed Silicon Valley startup building a real-life 'Jarvis'. An AI Copilot for design and manufacturing. Our goal is to utilize advanced AI, physics simulation, and computer graphics to reduce costs and improve engineering productivity across all steps of the design and manufacturing process.
 
 

On this Role:

This role is a mix of a few worlds coming together. You’ll be working with machine learning but not in a vacuum it’s applied to real engineering problems, working with 2D and 3D data from CAD, CAE, and CAM systems. A big part of the work is taking complex geometry, design workflows, and simulation data and figuring out how to turn that into something an AI system can actually understand and use.

We’re looking for someone who’s strong technically, especially in Python and ML, but also has the curiosity to dig into how things are designed and built in the real world. You might come from a research background or industry but either way you’re comfortable moving between theory and practical application. If you’ve spent time around mechanical systems or engineering design, that’s a big plus, because a lot of this role is about bridging that gap between advanced models and how engineers actually work day to day.

 

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.

What we are looking for

  • 5+ years of academic or industry experience in one or more of the following areas: Geometric Processing, Simulation, Optimization, Machine Learning, or Domain-Specific Languages.
  • BSc or MSc in Computer Science, Engineering, or a related field.
  • Proficient in writing clean, modular, and maintainable Python code.
  • Experience with dataset creation and data pipeline development.
  • PhD or MS with a focus in Computational Design, Simulation, or AI.
  • Experience developing CAD/CAM/CAE software tools.
  • Experience developing or fine-tuning large language models (LLMs), including post-training methods such as quantization, pruning, distillation, or reinforcement learning.
  • Experience designing or implementing DSLs or compilers.

Skills Required

  • 5+ years of experience in Geometric Processing, Simulation, Optimization, or Machine Learning
  • BSc or MSc in Computer Science, Engineering, or related field
  • Proficiency in Python programming
  • Experience with dataset creation and data pipeline development
  • Experience developing CAD/CAM/CAE software tools
  • Experience with large language models and post-training techniques
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The Company
HQ: Los Altos, California
27 Employees
Year Founded: 2023

What We Do

Meet the Al platform to Revolutionize Engineering. We started this company because manufacturing and engineering are overdue for a digital revolution. These fields are complex, and while agile, lean, and just-in-time methods have driven progress, AI now offers a transformative opportunity to reshape how work gets done. Foundation’s EGI platform is built to accelerate every stage of the product development cycle—from research and design to manufacturing and documentation—empowering engineers to build better products, faster and more efficiently.

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