Applied Researcher, Dexterous Manipulation

Your New Role and Team Sanctuary AI–a multi award-winning LinkedIn Top Startup company–is seeking an exceptional Applied Researcher, Dexterous Manipulation to join our team in engineering and innovating unique robotic manipulation tasks.

As an Applied Researcher, you'll be responsible for selecting the most promising state of the art (SOTA) approaches, designing training and data-collection pipelines, supervising the process of testing these algorithms in simulation, and deploying them to our robots in real-world settings. With access to in-house robots with dexterous hands, you'll also have a unique opportunity for impactful work with new haptic and proprioceptive sensing modalities.

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 SOTA RL/IL methodologies and robotics
• Identify, communicate, and drive promising research directions to the team
• Find ways of improving existing implementations of RL/IL learning 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****Qualifications- PhD in Machine Learning, Computer Science, Applied Math, or equivalent work experience in ML

• 3+ years' experience implementing and deploying (dexterous) robotic manipulation tasks in simulation and on physical robots
• Proven expertise in sim-to-real transfer
• Experience taking ML R&D and trained models into production
• Hands-on experience integrating ML models onto a robotics platform
• Experience with computer vision systems
• Publications in leading AI conferences such as ICRA, IROS and CORL

Skills- Extensive knowledge of Reinforcement Learning and Imitation Learning principles and use

• Development with Python 3.8 or later
• Working knowledge of PyTorch and/or TensorFlow
• Familiarity with ROS2
• Experience with Atlassian tools; Jira, Confluence, or equivalent i.e. GitLab

Traits- Above all else, a consistently positive attitude and a willingness to do whatever it takes to create robust solutions to complex problems

• Strong leadership skills in organizing R&D work for ML projects
• Eager to take on new challenges with tenacity and positivity
• Patience, persistence, and attention to detail when resolving performance issues
• Enthusiasm for bringing human-like intelligence to machines
• Ability to drive development of new functionalities from concept to production
• Ability to multitask and prioritize in a fast paced environment