Research Engineer, Deployment Performance, Robotics, DeepMind
Google DeepMind · London, England, United Kingdom
- On site
- Full-time
- $150,000 / year
- London, England, United Kingdom
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Job highlights
- Deploy and optimize AI models for robotics research.
- Develop scalable serving infrastructure for Gemini Robotics.
- Collaborate with global research and engineering teams.
- Focus on model performance and inference on TPUs.
- Contribute to advancing AI for physical world challenges.
About the role
About Google DeepMind
At Google, research-focused Software Engineers are embedded throughout the company, allowing them to setup large-scale tests and deploy promising ideas quickly and broadly. Ideas may come from internal projects as well as from collaborations with research programs at partner universities and technical institutes all over the world. From creating experiments and prototyping implementations to designing new architectures, engineers work on real-world problems including artificial intelligence, data mining, natural language processing, hardware and software performance analysis, improving compilers for mobile platforms, as well as core search and much more. But you stay connected to your research roots as an active contributor to the wider research community by partnering with universities and publishing papers. This role is within the Model Lifecycle Engineering team at DeepMind Robotics, which plays a critical role in the mission to solve AGI in the physical world. We develop and maintain scalable platforms to train, evaluate, and deploy Gemini Robotics models. By enabling researchers and Gemini Robotics trusted testers to iterate quickly and efficiently, we accelerate the pace of innovation in robotics research. As a Research Engineer, you will work closely with research scientists, engineers, and other stakeholders across DeepMind to develop and maintain the robust and scalable serving infrastructure that powers our robotics research. You will focus on building reliable and flexible serving solutions for real robot evaluation, accelerating both research and Gemini Robotics partners. You will learn and work in a fast-changing environment and collaborate with engineers and researchers from multiple teams across different time zones. Artificial intelligence will be one of humanity’s most transformative inventions. At DeepMind, we are a pioneering AI lab with exceptional interdisciplinary teams focused on advancing AI development to solve complex global challenges and accelerate high-quality product innovation for billions of users. We use our technologies for widespread public benefit and scientific discovery, ensuring safety and ethics are always our highest priority. We are pushing the boundaries across multiple domains. Our global teams offer learning opportunities and varied career pathways for those driven to achieve exceptional results through collective effort.Responsibilities
- Optimize and maintain serving setups for various environments, including research, on-premise, and on-device deployment.
- Conduct performance analysis, profiling, and optimization for serving robotics models.
- Collaborate effectively with a large team to meet ambitious research goals in a fast-moving environment.
Minimum Qualifications
- Bachelor's degree in Computer Science, Mathematics, a related field, or equivalent practical experience.
- 5 years of experience with machine learning frameworks (e.g., JAX, PyTorch).
- 2 years of experience in Python.
- 2 years of experience in optimizing for model performance, with a focus on inference on TPUs.
- 2 years of experience in building, profiling, and optimizing systems.
- 1 year of experience in C++.
Preferred Qualifications
- 1 year of experience with related infrastructure (e.g., Servo, One Platform, Gemax, Scaffolding, Uniserve, etc.).
- 1 year of experience with robotics or control systems.
Key skills/competency
- Robotics
- Deep Learning
- Performance Optimization
- Machine Learning Frameworks
- Python
- C++
- TPU Inference
- System Profiling
- Research Engineering
- Deployment
Skills & topics
- Research Engineer
- Robotics
- Deployment Performance
- Machine Learning
- AI
- Deep Learning
- TPU
- Python
- C++
- System Optimization
- JAX
- PyTorch
- Performance Engineering
- Software Engineering
- Google DeepMind
How to get hired
- Tailor your resume: Highlight experience with machine learning frameworks (JAX, PyTorch), Python, C++, and TPU optimization. Quantify achievements in system building and performance tuning.
- Showcase relevant projects: Emphasize any experience in robotics, control systems, or related infrastructure. Detail your contributions and the impact of your work.
- Prepare for technical interviews: Be ready to discuss algorithms, data structures, system design, and your experience with model performance optimization and profiling.
- Understand DeepMind's mission: Research their work in AI, robotics, and AGI. Be prepared to articulate your passion for advancing AI and solving complex global challenges.
Technical preparation
Master machine learning frameworks like JAX and PyTorch.,Practice Python and C++ for performance optimization.,Study TPU inference and model optimization techniques.,Review system profiling and building best practices.
Behavioral questions
Describe a complex performance optimization challenge.,How do you collaborate with researchers?,Discuss your experience with fast-paced environments.,Explain your approach to ethical AI development.
Frequently asked questions
- What specific machine learning frameworks are prioritized for this Research Engineer role at Google DeepMind?
- This Research Engineer position at Google DeepMind prioritizes experience with machine learning frameworks such as JAX and PyTorch. Demonstrating proficiency and practical application of these frameworks in your background will be highly beneficial.
- What is the expected level of Python and C++ experience for the Research Engineer role at DeepMind Robotics?
- For this Research Engineer role, Google DeepMind requires at least 2 years of experience in Python and 1 year of experience in C++. These are key languages for system building and optimization in this position.
- How does Google DeepMind approach performance optimization for robotics models in this role?
- Google DeepMind focuses on optimizing model performance, especially for inference on TPUs, for this Research Engineer role. You will be involved in building, profiling, and optimizing systems to achieve this goal.
- What kind of infrastructure experience is considered valuable for the Research Engineer, Deployment Performance position?
- For the Research Engineer, Deployment Performance role at Google DeepMind, experience with related infrastructure such as Servo, One Platform, Gemax, Scaffolding, Uniserve, etc., is preferred, with 1 year of experience being ideal.
- Does this Research Engineer role at DeepMind Robotics involve hands-on robotics experience?
- Yes, Google DeepMind prefers candidates with 1 year of experience in robotics or control systems for this Research Engineer position. This experience is valuable for developing and deploying AI models in the physical world.
- What are the key responsibilities of a Research Engineer in Deployment Performance at Google DeepMind?
- Key responsibilities include optimizing and maintaining serving setups, conducting performance analysis and profiling for robotics models, and collaborating with a large team to achieve ambitious research goals in a fast-moving environment.
- What is the educational background typically required for a Research Engineer at Google DeepMind?
- A Bachelor's degree in Computer Science, Mathematics, a related field, or equivalent practical experience is the minimum educational qualification for this Research Engineer role at Google DeepMind.