Software Engineer, Applied Robotics
Job Description
Snapshot
The Google Deepmind Robotics ML-Framework team's mission is to enable and accelerate cutting-edge robotics AI research and maximize research impact in the real world.
We achieve this by collaborating closely with top tier embodied AI researchers to tackle emerging challenges and push the boundaries of what’s possible. We form partnership with top robotics players in the world and actively work with them to externalize our robotics research outcome. Our team works hand in hand with infrastructure experts in robotics and GDM to deliver innovative, robust, flexible, and extensible software solutions that empower a wide array of research and partner projects.
The team is a core member of Google Deepmind Robotics, which is a research team devoted to exploring how machine learning can revolutionize the world of robotics. Recent advances in Large Language Models and perception, fueled by the deep learning revolution, have made it possible to envision autonomous robots that acquire a deep understanding of their environment through sensing and learning. This requires new, scalable approaches to learning in the physical world, as well as safe and data efficient approaches to continuously improving sensorimotor skills, which will ultimately enable autonomous agents to safely act in human-centered environments.
See this blog post and tech landing page to learn more about Robotics team's recent research advances and our plan of accepting sign up of trusted testers.
About us
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
As a Software Engineer in the Applied Research effort, you build infrastructure to enable partners to access our model development pipeline, deploy our latest AI robotics models to partners applications. You are insightful and innovative, preemptively discover needs and bottlenecks and propose, craft solutions iteratively with the team. You are the nexus between robotics team and partners, collaborate with cross-functional colleagues, provide engineering insights into research projects and bring understanding of partner's application need into engineering of tools.
Key responsibilities
- Work closely with robotics partners and trusted testers to bring state of the art Gemini robotics models to real world applications.
- Build and maintain reliable, flexible and easy to use infrastructure for robotics partners and trusted tester to develop robotics customized models and applications with of Gemini Robotics models.
- Analyze, identify and resolve system bottlenecks, tackle novel engineering challenges throughout the full system stack.
- Collaborate with robotics and GDM-wide infrastructure teams to define short and long-term infra roadmaps.
About you
Minimum qualifications:
- Passionate about robotics and foundation models. Eager to accelerate application of the Gemini robotics models working with external partners.
- Experience with Google and Deepmind frameworks for model training, evaluation, workflow management and data processing, etc OR experience with development in Google Cloud and One platform.
- Solid python/C++ programming experience in production environment.
- A team player with product mindset, willingness to learn, work with research and product colleagues, focus on delivering value in real-world applications.
Preferred qualifications:
- Bachelor’s, Master or Ph.D. degree in Computer Science, a related technical field, or equivalent practical experience.
- Full-stack development with production applications, including scoping, design, implementation, testing, debugging, releasing, deployment, etc.
- Experience with applying robotics ML/AI research to real-world problems and demonstrating impact.
- Collaboration experience with cross functional and cross organizational teams.