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Snapshot

Artificial Intelligence could be one of humanity’s most useful inventions. At Google DeepMind, we’re a team of scientists, engineers, machine learning experts and more, working together to advance the state of the art in artificial intelligence. We use our technologies for widespread public benefit and scientific discovery, and collaborate with others on critical challenges, ensuring safety and ethics are the highest priority.

The Role

We are seeking a Robotics Reliability Engineer to join our dynamic Robotics Research Engineering team. You will work closely with other software engineers and robotics AI researchers to ensure the reliability, performance, and observability of our robot software systems and to proactively improve our workflows. Your primary focus will be to enhance our robot data collection and AI policy evaluation reliability by identifying and resolving issues across the robotics stack, and support significant horizontal scaling.

Key responsibilities:

• Develop and utilise metrics to pinpoint systemic issues and prioritise their resolution, addressing areas such as hardware failures, cell reset/reconfiguration, debugging / visibility, deployment, and data quality.
• Work with researchers, software engineers and operators to identify, prioritise, debug and solve these and other workflow-related issues, e.g. in our robotic setups, ROS nodes, deployment mechanisms.
• Proactively design reliable tools for monitoring and deploying robotics systems at scale.
• Leverage external and internal tools to streamline the diagnosis and management of our robot fleet and workstations.

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:

• A background in software engineering or site reliability engineering.
• Experience building, deploying, running and debugging distributed systems.
• A passion for robotics and a desire to improve the reliability and performance of complex robotic systems.
• Experience developing and utilising metrics to monitor system health and identify areas for improvement.
• A collaborative mindset, as this role requires close collaboration with software engineers, AI researchers, and other stakeholders.

In addition, the following would be an advantage: 

• Familiarity with ROS (Robot Operating System), other robotics middleware, or a willingness to learn.
• Familiarity with open-source software and tools, especially related to deployment.
• Experience with some of: Python; C++; Docker; Shell scripting; Cloud infrastructure
• Capacity to analyse complex systems and find solutions to failures that have a cascading effect on the whole-pipeline.
• Familiarity with firmware and hardware, especially related to understanding root causes related to failures.