Research Scientist - Geometry & Machine Learning

REQUIRED: MUST have experience with Code Development. Applicants will not be considered without this experience.

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

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

This range represents base compensation only and is intended to provide flexibility for candidates with varying levels of experience, expertise and demonstrated impact. Final compensation will be determined based on factors including skills, experience, location,and overall alignment with the role.

In addition to base salary, eligible employees may receive:

• Equity participation in the company's long-term success
• Comprehensive benefits package including medical, dental and vision coverage
• Retirement savings benefits
• Generous paid time off and company holidays
• Remote-first work environment
• Fully funded company offsites and team gatherings
• Professional development and learning opportunities
• Home office support and remote work resources

We believe compensation should grow alongside impact. Our salary ranges are intentionally designed to provide room for career progression, increased scope of responsibility and continued growth within Foundation EGI.