Principal AI Research Scientist Post-Training · Alignment · Reinforcement Learning Autodesk AI Lab: London · San Francisco · Toronto · Remote (US/CA/EU
Remote · New York City, New York, United States or San Francisco, California, United States
Job Summary
Lead post-training for model development — from RLHF and preference optimization to agentic systems and long-horizon reasoning. Develop novel algorithms to improve model reliability, controllability, and alignment. Make principled architectural decisions about when to address challenges at pre-training, post-training, or system level. Design and run experiments shaping 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.
Required Qualifications
- A PhD or equivalent depth of industry research experience in ML, RL, AI, or a related field
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