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The Role
Work on designing, implementing, and improving state-of-the-art reinforcement and imitation learning algorithms for dexterous robotic manipulation. Develop RL/IL training and data-collection pipelines, integrate ML models onto robotics platforms, evaluate sim-to-real transfer, and collaborate across teams to deploy algorithms on physical humanoid robots.
Summary Generated by Built In
Your New Role and Team
Sanctuary AI, a world leader in building dexterity-driven Physical AI for general purpose robots, is looking to hire a skilled and motivated intern to join our ML team and contribute to our team’s work in engineering and innovating unique robotic manipulation tasks.
Reporting to the RL Lead, you will have the opportunity to tackle a variety of challenges related to the perception, planning, and motion systems for humanoid general-purpose robots.
The best candidates for this role have excellent software development and machine learning skills as well as hands-on experience with robotics. In this role you’ll be a valued contributor and you’ll gain a comprehensive understanding of the design, architecture, and implementation of the simulation platform and machine learning systems that power our general-purpose robots.
We are flexible regarding both the internship start date and the duration of the term.
Our Success Criteria
- Design, implement, and improve state-of-the-art Reinforcement Learning (RL) and Imitation Learning (IL) algorithms and test them in real-world settings
- Keep up to date with state-of-the-art RL/IL methodologies and robotics
- Identify, communicate, and drive promising research directions to the team
- Find ways of improving existing implementations of RL/IL pipelines with regards to standard metrics such as sample efficiency, speed, computational resource usage, and scalability
- Design RL/IL training and data-collection pipelines to facilitate fast deployment on physical robots
- Work with a multidisciplinary team to develop novel algorithms and investigate sources of errors with existing implementations
Your Experience
Desired Qualifications
- Pursuing MS or Ph.D. in Machine Learning, Computer Science, Applied Math, or related field
- Experience implementing a variety of RL and IL methods with a focus in a specialization such as computer vision or robotics
- Hands-on experience integrating ML models onto a robotics platform
- Experience implementing and deploying (dexterous) robotic manipulation tasks in simulation and on physical robots
- Experience taking ML R&D and trained models into production
- Experience with computer vision systems
- Experience in simulation-to-reality transfer learning
Skills
- Development with Python 3.6 or later
- Working knowledge of PyTorch and/or JAX
- Familiarity with ROS2
- Extensive knowledge of RL/IL principles and use
Traits
- Above all else, a consistently positive attitude and a willingness to do whatever it takes to create robust solutions to complex problems
- Optimistic listening and conflict resolution capabilities
- Demonstrated ability to influence others without authority
- Eager to take on new challenges with tenacity and positivity
- Patience, persistence, and attention to detail when resolving performance issues
- Obsession with bringing human-like intelligence to machines
Skills Required
- Pursuing MS or Ph.D. in Machine Learning, Computer Science, Applied Math, or related field
- Excellent software development and machine learning skills
- Experience implementing a variety of reinforcement learning (RL) and imitation learning (IL) methods
- Hands-on experience integrating ML models onto a robotics platform
- Experience implementing and deploying dexterous robotic manipulation tasks in simulation and on physical robots
- Experience taking ML research and trained models into production
- Experience with computer vision systems
- Experience in simulation-to-reality (sim-to-real) transfer learning
- Development experience with Python 3.6 or later
- Working knowledge of PyTorch and/or JAX
- Familiarity with ROS2
- Extensive knowledge of RL/IL principles and use
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The Company
What We Do
Sanctuary is on a mission to create the world’s first human-like intelligence in general-purpose robots that will help us work more safely, efficiently, and sustainably. And in the not-too-distant future, help us explore, settle, and prosper in outer space. Members of the Sanctuary team founded D-Wave (a pioneer in the quantum computing industry), Kindred (first use of reinforcement learning in a production robot), and the Creative Destruction Lab (pioneered a revolutionary method for the commercialization of science for the betterment of humankind). The team has experience launching market-defining innovations rooted in previously unsolved and deep scientific problems.
