Research Software Engineer- ML for Manufacturing (Computational Design & Geometry Processing)

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.

 

 

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.

 

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.

 

 

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.