Research Engineer, Applied Robotics

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 Research Engineer in the Applied Research team, you will build infrastructure that enables partners to access our model development pipeline and deploy our latest AI robotics models to their applications. You are insightful and innovative, proactively identifying needs and bottlenecks while proposing and iteratively crafting solutions with the team. You serve as the nexus between the robotics team and our partners—collaborating with cross-functional colleagues, providing engineering insights into research projects, and translating partners’ application needs into effective tool development.

Key responsibilities

• Work close with robotics partners and trusted testers to bring state-of-the-art Gemini robotics models to real-world applications.
• Explore, implement and optimize model flywheel recipes that enables robotics partners and trusted testers to develop customized models and applications using Gemini Robotics models.
• Build and maintain flexible and easy to use model development pipelines for trusted tester to develop robotics customized models and applications with of Gemini Robotics models.
• Analyze, identify, and resolve system bottlenecks while tackling novel engineering challenges across the full system stack.
• Collaborate with robotics and GDM-wide infrastructure teams to define short- and long-term infrastructure roadmaps.

About you

Minimum Qualifications:

• Passionate about robotics and foundational models, with a strong desire to accelerate the application of Gemini robotics models in collaboration with external partners.
  
  
• Experience with Google and DeepMind frameworks for model training, evaluation, workflow management, and data processing, or experience with development on Google Cloud and One Platform.
  
  
• Solid Python and C++ programming experience in a production environment.
  
  
• A team player with a product mindset, a willingness to learn, and the ability to work closely with research and product colleagues—always focused on delivering value in real-world applications.

Preferred Qualifications:

• Bachelor’s, Master’s, or Ph.D. degree in Computer Science, a related technical field, or equivalent practical experience.
  
  
• Experience in full-stack development for production applications, including scoping, design, implementation, testing, debugging, release, and deployment.
  
  
• Proven ability to apply robotics ML/AI research to real-world problems and demonstrate tangible impact.
  
  
• Collaborating experience with cross functional and cross organizational teams.