Job Description
Position Overview
Autodesk's domains — architecture, engineering, construction, manufacturing, media & entertainment — provide a distinctive research environment: rich structured data, long‑horizon reasoning tasks, and real‑world evaluation grounded in professional workflows.
Uniquely, decades of investment in physics simulation engines, CAD kernels, and computational design tools give us something most labs don't have: high‑fidelity, domain‑grounded verifiers that can serve as reward signals for post‑training. Rather than relying solely on human preference data, we can ground reinforcement learning in the laws of physics and the constraints of real engineering. These are exactly the kinds of challenges — and assets — that make post‑training and alignment research at Autodesk genuinely distinctive.
We publish at NeurIPS, ICML, ICLR, CVPR, and SIGGRAPH; collaborate with leading academic and industry labs; and have a direct line from research advances to p...