Your New Role and Team

Sanctuary, a world leader in building AI-based control systems for intelligent robots, is seeking a Principal Scientist to support our next generation of robot learning capability. This role sits at the intersection of deep technical understanding and rigorous validation: you will push the boundary of what robots can learn to do, and you will run the experiments that show which approaches have real merit and are worth scaling into a production capability. Deep expertise in at least one or more areas of robot learning — RL and imitation learning, simulation and sim2real, data collection, or world and foundation models — and a working knowledge or awareness of the rest. This role begins with reviewing everything we are doing and introducing new approaches: you will scope and run focused, high-leverage projects, and bring in support as your work proves out. Successful projects will drive larger projects and more resources.

Our Success Criteria

- Identify, scope, and lead research initiatives, working with contributors from across the company
- Design and run experiments that validate early hypotheses, surfacing what works, what does not, and what deserves further investment
- Demonstrate the merit of new approaches through hands-on experimentation, building the evidence base that demonstrates readiness to scale toward production
- Ability to create, develop, and enhance cutting-edge robot learning algorithms — RL, imitation learning, world models, foundation models, or approaches we have not tried — and evaluate their performance in practical robotic applications
- Devise training and data collection pipelines to expedite implementation on physical robots
- Discover strategies for enhancing current learning processes,



considering key performance metrics like sample efficiency, speed, computational resources, and scalability
- Collaborate within a diverse team to devise, implement, and harden algorithms for production use, and investigate the root causes in existing implementations
- Translate Machine Learning research and trained models into real-world robotic products, working closely with engineering to validate that promising methods hold up as they move toward our cross-platform software framework
- Stay current with the latest developments in robot learning — including RL/IL, world models, and foundation models — and their application in robotics

- Your Experience

Qualifications

- Ph.D. in Machine Learning, Computer Science, Applied Mathematics, or equivalent practical background in robot learning
- 5+ years of hands-on experience implementing and deploying robotic manipulation tasks, both in simulation and on physical robots
- Experience transitioning Machine Learning research and trained models into real-world production
- Active involvement integrating Machine Learning models into a robotics platform
- Strong technical judgment and the ability to form and defend an independent point of view
- Independently able to evaluate a landscape, propose an approach, complete a proof-of-concept and document and articulate the results to a cross-functional team




- Comfortable challenging assumptions and driving alignment across technical stakeholders

Deep expertise in at least one of

- Applying various Reinforcement Learning and/or Imitation Learning methods, with focus on robotics in the real world
- Developing and optimizing large-batch parallel simulations, and proven expertise in sim-to-real transfer
- Designing and scaling data collection workflows and datasets for robot learning on physical systems
- Building or fine-tuning world models or foundation models for robotics

Nice to Have

- Proven expertise in continual learning, employing adaptive model training to improve long-term performance and accuracy
- Research contributions at venues such as ICRA, IROS, CoRL, or NeurIPS, or open-source work

Skills

- Development with Python 3.8 or later
- Working knowledge of PyTorch and/or TensorFlow

- Familiarity with ROS2
- Strong understanding of contemporary robot learning methods and their application

Traits

- Above all else, a consistently positive attitude and a willingness to do whatever it takes to create robust solutions to complex problems
- Pragmatic and outcome-oriented, with a bias toward turning advanced research into real-world products
- Entrepreneurial: comfortable scoping and running a project with a cross-functional team
- Strong leadership skills in organizing R&D; work for projects, with the ability to lead a cross functional team
- Curious, adaptable, and willing to go deep into unfamiliar technical areas when needed
- Patience, persistence, and attention to detail when resolving performance issues
- Ability to multitask and prioritize in a fast-paced environment

📌 Principal Scientist, Physical AI (Vancouver)
🏢 Sanctuary AI
📍 Vancouver