Senior Research Engineer, Generative 3D
Confirmed on the employer's own hiring board on Nov 9, 2026. First seen by Alion on Oct 28, 2026.
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About Mimo
MimoLabs builds Mimo, an agentic system for making physical things. Describe anything and Mimo helps you make it: he designs the geometry, simulates that it can be made, configures material, process and price, and routes it to production, across 3D printing, CNC, laser cutting and more. Mimo ships today as Mimo Studio for anyone regardless of skill, and we are building developer tools and enterprise solutions for more technical applications.
We are a VC funded, experienced technical team, based at Newlab in Detroit and remote across the US.
About the role
You will build the models and the training pipeline behind how Mimo generates manufacturable CAD and runs simulation, and you will lead the research practice that decides which methods we commercialize next. The work sits where generative 3D meets physics: shapes that come out of a generative prior and hold up under load, and the pipelines that train, evaluate and serve them. You will work alongside the computational geometry engineer, who owns the exact geometry and the analysis tools your models feed.
What you will do
Build and train the models that turn intent into manufacturable geometry across implicit, latent and B-rep targets, for example a part generated from a description and a load case.
Put physics in the loop: differentiable simulation and physics-driven optimization of generated shapes, for example a generated bracket optimized in the model's latent space until finite-element analysis says it holds.
Own the training pipeline end to end: data curation and licensing, pre- and post-training, checkpoints, and the evaluation suite that decides what ships, for example watertight and manifold rates, fidelity to the request, and cost per generation.
Build the understanding side: part segmentation, semantic classification and spatial comprehension of CAD and mesh data.
Run the research practice: read the field, reproduce the methods that matter, and write the go/no-go memo on each.
Take models to production with the team, with latency and cost measured.
You may be a good fit if you have
Published or shipped generative 3D: diffusion or flow models over implicit, voxel or latent-set representations, reconstruction, or latent-space optimization, with results you can show.
Differentiable simulation or physics-driven shape optimization, with finite elements or equivalent physics in the loop, in research or in production.
Training pipelines you built and ran end to end: data, training, evaluation and checkpoints, on multi-GPU hardware.
A record of either peer-reviewed publications (SIGGRAPH, CVPR, ICCV, NeurIPS or equivalent) or production models with measured results.
Clear writing: a memo a founder can act on.
Nice to have
Topology optimization and computational design (strong plus).
CUDA, Triton or Warp kernels you wrote or tuned; GPU serving with measured latency and cost.
B-rep and parametric CAD; CAD code generation.
Computational mechanics: finite elements, contact, material models; GPU solvers.
Differentiable rendering, Gaussian splatting, multi-view diffusion.
Rust.
How we work
Everyone here runs several AI coding agents on our own tooling, and everyone is free to extend that tooling and change how we build. We judge the work by the physical thing it produces: a part that prints, a toolpath that cuts, a quote that holds. We are fast and adaptable, honest with each other about what is working, and we celebrate the wins. We are a small team that loves what it is building. Research depth matters most for this role; prior experience with coding agents is not required.
Pay, equity and benefits
$170K-$220K base and equity, four-year vesting with a one-year cliff.
Health, dental and vision.
Logistics
Location: remote across the US; the company's home is Newlab in Detroit, with occasional travel there.
Work authorization: US work authorization is required, and we are not able to sponsor visas for this role. The role works with customer and partner data held under NDA and may require US-person status for export-control compliance.
Education: no degree requirement.
AI: we use AI tools to organize and summarize applications; a person reads every application and makes every decision. Use AI to prepare yours if you like; the short answers in the form should be your own.
Process: a call with a founder, a technical conversation on a real problem from the role, a conversation with the team, references, offer.
Safety: we only write from mimolabs.ai addresses and never ask for money, fees or banking details before your first day.
How to apply
Apply on our careers page at mimolabs.ai/careers.
MimoLabs is an equal-opportunity employer.