Research Lead / Principal Scientist & Manager Post-Training · Alignment · Reinforcement Learning Autodesk AI Lab: Toronto · Remote (CA)
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About the Role
Autodesk AI Lab seeks a Research Lead to own post-training and alignment strategy for foundation models. You will lead a team of AI scientists, develop novel algorithms, and publish at top venues.
Key Skills for This Role
Responsibilities
- 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
- 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
- Manage, mentor, and grow a team of AI scientists
- Set technical direction and research priorities across post training and alignment initiatives
Requirements
- 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
- Strong intuition for model behavior, alignment challenges, and post training trade offs
- Experience designing evaluation systems and thinking rigorously about model readiness
- Ability to communicate complex technical trade offs clearly to both technical and non technical audiences
- PhD or equivalent depth of industry research experience in ML, RL, AI, or a related field
Full Job Posting
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.
- 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.
- 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.
Responsibilities
- 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
- 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
- Manage, mentor, and grow a team of AI scientists
Minimum Qualifications
- 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
Preferred Qualifications
- 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
The Ideal Candidate
- 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
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