Sanctuary2mo ago

Machine Learning Research Intern (Reinforcement/Imitation Learning)

Vancouver · VancouverInternentry

Data ScienceMachine LearningData & AI

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Quick Summary

Overview

Your New Role and Team Sanctuary AI, a world leader in building dexterity-driven Physical AI for general purpose robots,

Technical Tools

Data ScienceMachine LearningData & AI

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.

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