Job Requisition ID #
26WD98298
Research Lead / Principal Scientist & Manager
Post-Training · Alignment · Reinforcement Learning
Autodesk AI Lab: London · San Francisco · Toronto · Remote (US/CA/EU)
Open to Remote: Germany, France or Italy
The Opportunity
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 remain close to the work.
You will lead a growing team of AI scientists while continuing to contribute directly to research: running experiments, developing novel algorithms, and publishing at top-tier venues.
This role reports to the Senior Director of AI Research within Autodesk AI Lab.
Why This Role
Unique research surface area
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 here genuinely distinctive.
Research-first, with real impact
We publish at NeurIPS, ICML, ICLR, CVPR, and SIGGRAPH. We collaborate with leading academic and industry labs. And we have a direct line from research advances to product impact at scale. This is not a role where research sits behind a wall from engineering — you will see your work matter.
What You Will Do
Research & Technical Leadership
- Own post-training strategy for model development — from RLHF and preference optimization to agentic systems and long-horizon reasoning
- Develop novel algorithms that improve model reliability, controllability, and alignment
- Make principled architectural decisions about when to address challenges at the pre-training, post-training, or system level
- Design and run experiments that shape model behavior, robustness, and reasoning quality
- Partner with infrastructure teams to build scalable, reproducible post-training workflows
- Contribute to publications, patents, and Autodesk's external research visibility
Evaluation & Model Quality
- Design 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
Team & Organizational 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
What We Are Looking For
We care about research judgment and outcomes, not credential checklists. Strong candidates will typically have:
- Deep hands-on expertise in reinforcement learning for foundation models, and fluency with post-training methods (RLHF, RLAIF, DPO, PPO, or adjacent approaches)
- Proven experience leading or mentoring technical research teams — whether in an academic lab, AI research organization, or industry setting
- Strong intuition for model behavior, alignment challenges, and post-training trade-offs
- Experience designing evaluation systems and thinking rigorously about what it means for a model to be ready
- Ability to communicate complex technical trade-offs clearly to both technical and non-technical audiences
- A PhD or equivalent depth of industry research experience in ML, RL, AI, or a related field
We also value, but do not require:
- Experience at a frontier model lab or advanced applied AI organization
- A strong publication record at leading ML or AI venues
- Background in alignment research, preference learning, or agentic AI
- Experience deploying or supporting production AI systems
- Familiarity with large-scale training infrastructure and compute trade-offs
What Success Looks Like
In the first year, success means:
- Post-trained models show measurable improvements in reliability, alignment, reasoning quality, and domain usefulness
- Evaluation metrics and release criteria are trusted and adopted across teams
- The team delivers high-quality research with practical impact — and team members are growing into stronger, more independent researchers
- Leadership relies on your judgment for model readiness, technical direction, and risk assessment
- Autodesk AI Lab advances its reputation as a serious contributor to frontier AI research
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.
Learn More
About Autodesk
Welcome to Autodesk! Amazing things are created every day with our software – from the greenest buildings and cleanest cars to the smartest factories and biggest hit movies. We help innovators turn their ideas into reality, transforming not only how things are made, but what can be made.
We take great pride in our culture here at Autodesk – it’s at the core of everything we do. Our culture guides the way we work and treat each other, informs how we connect with customers and partners, and defines how we show up in the world.
When you’re an Autodesker, you can do meaningful work that helps build a better world designed and made for all. Ready to shape the world and your future? Join us!
Salary transparency
Salary is one part of Autodesk’s competitive compensation package. Offers are based on the candidate’s experience and geographic location. In addition to base salaries, our compensation package may include annual cash bonuses, commissions for sales roles, stock grants, and a comprehensive benefits package.
Diversity & Belonging We take pride in cultivating a culture of belonging where everyone can thrive. Learn more here: https://www.autodesk.com/company/diversity-and-belonging
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