We are hiring for this role in Mountain View, New York or London.
Snapshot
We are looking for an Operational Safety Engineer to join the Google DeepMind Robotics team. The engineer will collaborate with researchers to perform safety risk assessments, implement state of the art safety solutions on our robots and workcells, inform and guide safety policies and documentation, and help accelerate the development of emerging robotics capabilities.
About Us
At Google DeepMind Robotics, we’re a team of scientists, engineers, machine learning experts and more, working together to advance the state of the art in AI-enabled Collaborative Robots. Our mission is to responsibly build “Embodied AI” - a robot brain capable of turning natural language instructions into useful physical actions in human-centric environments - to improve the lives of billions of people in the physical world.
The Role
Operational Safety is a critical facet of responsible development of AI-enabled collaborative robots for human-centric environments. Typical work will include:
- Performing Hazard and Risk Analysis for emerging Robotics Platforms
- Provide expertise and guidance on Implementing state-of-the-art safety solutions on our robots and workcells, to enable safe data collection and model evaluation
- Working closely with Google DeepMind Robotics Researchers to accelerate development of new capabilities while ensuring safety.
- Coordinating with Environment, Health and Safety (EHS) teams to ensure consistency across GDM Robotics Labs.
- Preparing Safety training materials
- Helping evolve safety standards for AI-enabled collaborative robots
About You
In order to set you up for success as at Google DeepMind, we look for the following skills and experience:
- Experience working with real-world robots, preferably Humanoid platforms
- Strong exposure to Machine Learning/AI systems and research
- Experience on solving practical Safety challenges, performing Risk Assessments and Hazard Analysis; knowledge of STPA techniques would be a plus.
- Working with different stakeholders to define and implement safety guidelines to ensure the safety of humans and robots in mixed environments, and also ensure that research velocity is not compromised
- Understanding of ISO/RIA Safety Standards
- BS or MS in Computer Science, Robotics or Systems Safety Engineering is preferred but not necessary with equivalent practical experience
In addition, the following would be an advantage:
- PhD in Computer Science, Robotics or Systems Safety Engineering is preferred but not necessary with equivalent practical experience
- Publication track record in Robotics and/or Safety
The US base salary range for this full-time position is between $161,000 - $275,000 + bonus + equity + benefits. Your recruiter can share more about the specific salary range for your targeted location during the hiring process.
At Google DeepMind, we value diversity of experience, knowledge, backgrounds and perspectives, and harness these qualities to create extraordinary impact. We are committed to equal employment opportunity regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, pregnancy, or related condition (including breastfeeding) or any other basis as protected by applicable law. If you have a disability or additional need that requires accommodation, please do not hesitate to let us know.
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What We Do
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. Our long term aim is to solve intelligence, developing more general and capable problem-solving systems, known as artificial general intelligence (AGI). Guided by safety and ethics, this invention could help society find answers to some of the world’s most pressing and fundamental scientific challenges. We have a track record of breakthroughs in fundamental AI research, published in journals like Nature, Science, and more.Our programs have learned to diagnose eye diseases as effectively as the world’s top doctors, to save 30% of the energy used to keep data centres cool, and to predict the complex 3D shapes of proteins - which could one day transform how drugs are invented.
