Research Lead / Principal Scientist & Manager Post-Training · Alignment · Reinf

Job Requisition ID # 26WD98297 26WD98297, Research Lead / Principal Scientist & Manager Post-Training · Alignment · Reinforcement Learning Autodesk AI Lab: Toronto · Remote French translation to follow! /Traduction française à suivre!

About Autodesk AI Lab Autodesk AI Lab advances state-of-the-art research across generative AI, multimodal foundation models, reasoning systems, and human-AI collaboration. Our work has direct impact across the industries that shape the physical world.

We are an active contributor to the global research community and collaborate closely with leading academic and industry labs. At Autodesk , we are building a diverse workplace and an inclusive culture to give more people the chance to imagine, design, and make a better world.

Autodesk is proud to be an equal opportunity employer and considers all qualified applicants for employment without regard to race, color, religion, age, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other legally protected characteristic.

Position Overview Foundation models are reshaping how engineers, architects, and designers work — but training foundation models that are reliable, domain-capable systems is still an open research problem. Autodesk touches more of the physical world than almost any other software company.

The products we build are used to design skyscrapers, manufacture aircraft, and produce films. AI is now central to how those workflows are evolving — and post-training is the layer that makes the difference between a capable model and one that is dependable and robust in our customers’ high-precision domains.

As Research Lead for Post-Training & Alignment, you will own Autodesk 's research strategy for transforming foundation models into systems that are reliable, aligned, and genuinely useful in complex, domain-specific workflows.

This is a deeply technical leadership role — you will shape research direction, drive key architectural decisions, and