Research Engineer, Robotics

About Us

In the robotics team we believe that a truly general AI needs to be able to act in the physical world. The aim of the Robotics Team is to embody Artificial Intelligence, thereby endowing it with the ability to learn how to interact with objects, people, and other robots, in order to perform complex and useful tasks. At Google DeepMind, experts in different scientific fields (e.g. quantum chemistry, neuroscience, game theory) collaborate with research scientists and software engineers to solve grand challenges that would enable multiple scientific breakthroughs. The Robotics Lab is a group of pioneering research scientists, research engineers and software engineers uniquely specialised in Robotics at Deepmind.

The Role

Our Robotics Research Team at Google DeepMind focuses on Machine Learning approaches to robotics, with an emphasis on scalable and general techniques. We’re looking for Robotics Research Engineers to work on the development and deployment of new models and algorithms for robot perception, planning and control.

Google is uniquely positioned to offer AI technology to billions of users, and we’re particularly interested in candidates who are passionate about pushing technology to the real-world. The ideal candidate would have expertise in both the modern AI stack as well as theoretical and practical knowledge of robot control, and be comfortable communicating with external product teams.

The work that we do presents interesting and unique engineering challenges and as a member of the Research Engineering team, you’ll contribute towards enhancing the performance of both our research infrastructure and learning algorithms.

Key Responsibilities

• Work with a small team to develop and iterate on new techniques
• Write and maintain robotics R&D infrastructure
• Design and run experiments
• Evaluate results and communicate effectively to the wider team

About You

In order to set you up for success as a Research Engineer at Google DeepMind, we look for the following skills and experience:

• Modelling, planning and control for hybrid dynamical systems (i.e. systems that exhibits both continuous and discrete dynamic behaviours) with application to robotic manipulation
• Machine learning (SL, UL, RL) applied on simulated and real robots (with continuous action space and continuous state space)
• Middleware and software development for robotics. Experience with real-time middleware for robotics will be positively evaluated
• Robotics perception (e.g. object pose estimation and matching, instance segmentation, dense prediction, grasp detection, planning, end-to-end and self-supervised grasping, depth and ego-motion, etc.). Experience with deep learning for perception will be positively evaluated

In addition, the following would be an advantage:

• Experience with enterprise software development
• Experience with deploying real-world technology, e.g. product-teams, startups, open-source contributions