Foundation EGI

AI-powered platform for manufacturing optimization

Research Software Engineer: Simulation Algorithm/ Geometry Processing

Backend EngineeringConfirmed live in the last 24 hours

Full-time$100k - $140k /yrRemote

About the Job

Requirements

At least 5 years of academic or industry experience in one or more of geometric processing, simulation, optimization, machine learning, or domain-specific languages.
Proficiency in writing clean, modular, and maintainable Python code.
Experience with dataset creation and data pipeline development.
A PhD or master's degree focused in computational design, simulation, or AI.
Experience developing CAD/CAM/CAE software tools.
Experience developing or fine-tuning large language models, including post-training methods such as quantization, pruning, distillation, or reinforcement learning.
Experience designing or implementing domain-specific languages or compilers.
Experience with code development and computational design and/or geometry processing is required.

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.

Salary Range: 100000 to 140000 (Currency: USD) (Pay period: per-year-salary)

REQUIRED: MUST have experience with Code Development + Computational Design and/or Geometry Processing. 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.
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.

About the Company

Foundation EGI

AI-powered platform for manufacturing optimization

Foundation EGI builds an AI platform for manufacturing SaaS that uses a purpose-built LLM and agent-based AI to optimize the entire design-to-production lifecycle. The platform plugs into existing manufacturing workflows, analyzes data across design and production, and can automate actions or provide actionable recommendations to improve throughput, quality, and efficiency. It differentiates itself by leveraging deep expertise in computer graphics, computational design, and machine learning to offer an enterprise-grade, end-to-end solution tailored to manufacturing, not generic tools. Its goal is to modernize American manufacturing by delivering scalable AI-powered tools that streamline design-to-production processes and enable data-driven decision-making.

Company size: 11-50
Company stage: Series A
Total funding: $36.6M
Headquarters: Los Altos, CA
Founded: 2023

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