Autodesk

Technology

ResearchLead/PrincipalScientist&ManagerPost-Training·Alignment·ReinforcementLearning

Toronto, Ontario, Canada FULL TIME Remote Friendly
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Lead candidates.

The Brief

“Research Lead / Principal Scientist & Manager Post-Training · Alignment · Reinforcement Learning at Autodesk. Skills: Reinforcement Learning, Foundation models, Post-training, Alignment. Own post-training strategy for model development. Develop novel algorithms that improve model reliability, controllability,”

What You'll Achieve.

Models show measurable improvements in reliability, alignment, reasoning quality, and domain utility; Evaluation metrics and production readiness criteria are adopted by all teams; Team produces high-quality research with concrete impact; Team members become stronger, more autonomous researchers; Leadership relies on judgment for model readiness, technical direction, and risk assessment; Autodesk AI Lab strengthens reputation as major contributor to cutting-edge AI research

Industry & Context.

Technology
Problems you'll solve

Address challenges; Shape model behavior; Improve model reliability; Improve model controllability; Improve model alignment; Improve model robustness; Improve reasoning quality; Model analysis; Interpretability efforts; Troubleshooting

What They're Looking For.

Must Have

Deep hands-on expertise in reinforcement learning for foundation models, Fluency with post-training methods (RLHF, RLAIF, DPO, PPO, or adjacent approaches), Proven experience leading or mentoring technical research teams, Intuition for model behavior, alignment challenges, and post-training trade-offs, Experience designing evaluation frameworks for long-horizon reasoning, tool use, agentic behavior, safety, and real-world workflow completion, Lead rigorous model analysis and interpretability efforts, Drive human-in-the-loop evaluation with high annotation quality and sound scientific methodology, Establish model readiness criteria and provide go/no-go recommendations for releases, Communicate technical risks, limitations, and trade-offs clearly to leadership, Manage, mentor, and grow a team of AI scientists, Set technical direction and research priorities across post-training and alignment initiatives, Foster a research culture grounded in scientific rigor, reproducibility, and fast iteration, Help recruit world-class talent across ML, RL, alignment, and foundation models, Partner closely with pre-training teams, infrastructure, product organizations, and other stakeholders, Translate research trade-offs into clear, decision-ready guidance for leadership

Nice to Have

Experience in deploying or supporting AI systems in production, Knowledge of large-scale training infrastructures and compute trade-offs

What You'll Do.

Own post-training strategy for model development

Develop novel algorithms that improve model reliability

Make principled architectural decisions about when to address

Design and run experiments that shape model behavior

Partner with infrastructure teams to build scalable

Contribute to publications

and Autodesk's external research

Design evaluation frameworks for long-horizon reasoning

Lead rigorous model analysis and interpretability efforts

Drive human-in-the-loop evaluation with high annotation quality and

Establish model readiness criteria and provide go/no-go recommendations

Communicate technical risks

and trade-offs clearly to

and grow a team of AI

Set technical direction and research priorities across post-training

Foster a research culture grounded in scientific rigor

Help recruit world-class talent across ML

Partner closely with pre-training teams

product organizations

Translate research trade-offs into clear

decision-ready guidance for

How You'll Work.

Team & Collaboration

Partner with infrastructure teams; Partner with pre-training teams; Partner with product organizations; Partner with other stakeholders

Communication Scope

External research visibility; Technical risks communication; Limitation communication; Trade-off communication; Decision-ready guidance

Full Job Description

**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 architectu

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