Research Scientist, Robotics, DeepMind

The Google Cloud Platform team helps customers transform and build what's next for their business — all with technology built in the cloud. Our products are developed for security, reliability and scalability, running the full stack from infrastructure to applications to devices and hardware. Our teams are dedicated to helping our customers — developers, small and large businesses, educational institutions and government agencies — see the benefits of our technology come to life. As part of an entrepreneurial team in this rapidly growing business, you will play a key role in understanding the needs of our customers and help shape the future of businesses of all sizes use technology to connect with customers, employees and partners.

As a Capacity Management Lead, Forward Deployed Developing, you will focus on optimizing the deployment, utilization, and well-being of technical talent across AI Tech Go-to-Market teams. Operating as an individual contributor, you will own the end-to-end matchmaking process—aligning project requirements with consultant skill sets, availability, and constraints—while serving as a trusted advisor to practice managers and leadership. This role requires a data-driven, relationship-oriented professional who can seamlessly balance day-to-day tactical staffing with strategic forecasting and process improvement.

Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

Canada: $146000 - $150000 (CAD) + 15% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities

• Design, implement, train, and evaluate large models and algorithms for robotic agents to make breakthroughs and unlock new robot capabilities.
• Write software to implement research ideas and iterate quickly.
• Participate in a wide variety of research, including learning from simulation, reinforcement learning, learning from demonstrations, vision-language-action (VLA) models, transformers, video generation, robot control, humanoid robots, and more.
• Work effectively with a large collaborative team with changing agendas to meet ambitious research goals.
• Generate creative ideas, set up experiments, and test hypotheses to report and present research findings clearly and efficiently both internally and externally.

Qualifications

Minimum qualifications:

• PhD in Computer Science, a related field, or equivalent practical experience.
• Experience contributing to research communities or efforts, including publishing papers at conferences (e.g., NeurIPS, CoRL, ICML, ICLR).
• Experience working with simulators and robots.

Preferred qualifications:

• Experience training neural networks using large datasets or simulation to improve real robot behavior.
• Experience in robot manipulation.
• Experience with Python programming.