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 CriteriaIdentify, 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
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 modern 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
Sanctuary AI Vancouver, British Columbia, CAN Office
Vancouver, British Colombia, Canada
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