Research Lead / Principal Scientist & Manager Post-Training · Alignment · Reinforcement Learning Autodesk AI Lab in Canada Creek, Nova Scotia at Jobgether

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Research Lead / Principal Scientist & Manager – Post-Training · Alignment · Reinforcement Learning in Canada.

This role sits at the forefront of frontier AI research, focusing on transforming foundation models into reliable, aligned, and domain-ready systems. You will lead a growing team of AI scientists while remaining deeply hands-on in research, shaping post-training strategies that include reinforcement learning, preference optimization, and agentic reasoning systems. Operating within a highly advanced AI research environment, you will influence both long-term research direction and real-world product impact across industries such as architecture, engineering, manufacturing, and media. The position blends scientific leadership with execution, requiring strong judgment in model behavior, evaluation design, and alignment trade-offs. You will collaborate closely with infrastructure, product, and research teams to ensure scalable and reproducible training workflows. This is a high-impact leadership role where your work directly contributes to advancing trustworthy AI systems used in real-world professional workflows.

You will define and lead the post-training and alignment research strategy, overseeing how foundation models are refined into robust, safe, and high-performing systems. You will guide both technical direction and team execution while staying actively engaged in experimentation and algorithm development.

• Lead post-training strategy across RLHF, preference optimization, and reinforcement learning for complex reasoning systems
• Develop novel algorithms to improve model alignment, controllability, reliability, and domain-specific performance
• Design and execute experiments to evaluate model behavior, robustness, reasoning quality, and safety
• Establish evaluation frameworks for long-horizon reasoning, agentic behavior, and real-world workflow completion
• Define model readiness criteria and provide go/no-go recommendations for deployment
• Manage, mentor, and grow a team of AI researchers while fostering a high-rigor scientific culture
• Collaborate with infrastructure and product teams to build scalable and reproducible training systems
• Contribute to publications, patents, and external research visibility in top-tier ML venues
• Translate technical findings into clear guidance for leadership and cross-functional stakeholders

This role requires deep expertise in reinforcement learning and foundation model post-training, combined with proven research leadership experience. You should bring strong intuition for model behavior, alignment challenges, and large-scale AI system trade-offs.

• Extensive hands-on experience with reinforcement learning and post-training methods (RLHF, RLAIF, PPO, DPO, or similar)
• Proven experience leading or mentoring AI research teams in industry or academic settings
• Strong understanding of alignment challenges, model evaluation, and reasoning systems
• Experience designing rigorous evaluation frameworks for AI model performance and readiness
• Ability to communicate complex technical concepts and trade-offs to diverse audiences
• Background in ML, AI, or RL research, typically supported by a PhD or equivalent industry research experience
• Preferred experience in frontier AI labs, agentic AI, or alignment research
• Familiarity with large-scale training infrastructure and production AI systems is an asset
• Strong publication record in top ML venues is highly valued

• Competitive compensation package including base salary, bonus, and equity components
• Comprehensive health, dental, and vision coverage
• Inclusive and collaborative research environment focused on real-world impact
• Flexible work arrangements, including remote options across North America and Europe
• Strong emphasis on research freedom, publication, and external visibility
• Professional development opportunities and access to cutting-edge AI infrastructure
• Paid time off, wellness programs, and employee support initiatives
• Opportunity to influence frontier AI systems used in high-impact industrial domains