Software Engineer, Robotics

As a Software Engineer in Robotics at Google DeepMind, you'll tackle a range of responsibilities, including designing, implementing, and optimizing crucial software components for large-scale robotics and data systems. Your role will also involve developing and maintaining innovative test infrastructures, enhancing team productivity, and closely collaborating with cross-functional teams to drive research progress and bring embodied AI solutions to the real world.

To qualify for the Software Engineer position in Robotics at Google DeepMind, candidates should possess strong skills in C++ and Python, with experience in systems design, performance optimization, and debugging within complex environments. A generalist mindset with the capability to navigate a fast-changing environment and strong communication skills are essential, alongside a background in large codebases and software systems.

The expected salary range for a Software Engineer in Robotics at Google DeepMind in Mountain View is between $136,000 and $210,000, complemented by bonuses, equity, and a comprehensive benefits package. Specific compensation details will be discussed by your recruiter during the hiring process, allowing for transparency and alignment with your expectations.

At Google DeepMind, the work environment for Robotics Software Engineers is dynamic and collaborative. You'll engage in a team-oriented culture that encourages innovation and creativity. With a focus on advancing embodied AI responsibly, engineers work alongside scientists and researchers to tackle complex challenges, ensuring that safety and ethics are prioritized throughout.

Preferred experience for the Software Engineer position in Robotics at Google DeepMind includes a background in developing and optimizing large-scale data or machine learning pipelines, as well as expertise in designing and maintaining development or testing infrastructures for complex software systems. Experience with robotics software or embedded systems is also advantageous.

This question is your opportunity to show your passion for AI and robotics. Reflect on specific projects or values of Google DeepMind that resonate with you. Highlight your enthusiasm for contributing to groundbreaking technologies that positively impact society.

When answering this, focus on a specific example where you faced a technical challenge. Outline the problem clearly, the approach you took to troubleshoot, and the outcome. Emphasize your problem-solving skills and ability to work collaboratively in a team.

This question assesses your time management skills. Outline your approach to prioritizing tasks, such as using project management tools or frameworks like the Eisenhower Matrix, ensuring you emphasize your flexibility and ability to adjust priorities based on project needs.

Be prepared to discuss specific projects where you utilized C++ and Python. Mention the challenges you faced, your problem-solving strategies, and any optimizations you implemented. Emphasize how your experience aligns with the technical requirements of Google DeepMind.

Share examples of teamwork, highlighting specific instances where collaboration led to successful outcomes. Discuss tools and practices you've used to facilitate communication, such as version control systems, agile methodologies, or regular stand-ups.

Identify a key project where your contributions had a substantial impact. Discuss your role, technologies used, and the outcomes. This showcases your passion and expertise in robotics, emphasizing how you can contribute to Google DeepMind's mission.

Explain your systematic approach to debugging, such as breaking down issues step-by-step and using debugging tools and logs to trace problems. Provide examples if possible, showcasing your analytical skills.

This question allows you to demonstrate your understanding of the broader impact of technology. Discuss the importance of safety, ethics, and ensuring AI benefits society. Align your views with Google DeepMind's commitment to responsible AI development.

Share resources you use to stay informed, such as conferences, online courses, journals, or professional networks. Highlight any personal projects or continued learning you pursue, showing your commitment to growth in the field.

Detail your experience regarding machine learning pipelines. Focus on specific tools, languages, or frameworks you’ve used and discuss any projects that involved ML, showcasing how these experiences have prepared you for the role at Google DeepMind.