Staff GenAI Silicon Automation Engineer — Equity

Staff Software Engineer, GenAI Silicon Automation, DeepMind

Share Staff Software Engineer, GenAI Silicon Automation, DeepMind

corporate_fare DeepMind place Paris, France

Apply

info_outline

info_outline X

Google welcomes people with disabilities.

• Bachelor's degree in Computer Science, related technical field or equivalent practical experience.
• 5 years of experience in hardware design or test.
• 2 years of experience with software development in one or more programming languages.

Preferred qualifications:

• Master's degree or PhD in Computer Science or a related field with a focus on AI/ML.
• 8 years of experience coding in one programming language (e.g., Java, C++, Python, etc.).
  
• 5 years of experience with machine learning algorithms and tools (e.g., PyTorch, JAX, TensorFlow), artificial intelligence, deep learning, Large Language Model (LLMs), or natural language processing.
• 5 years of experience with data structures and algorithms and hardware-software co-design.
• 3 years of experience in low level ML accelerator programming, compiler or other close to hardware performance programming.

About the job

At Google DeepMind our mission is to build the world's first general-purpose learning agent. Central to this mission is the complex task of measuring the intelligence of our prototypes. As a Software Engineer, you will be working with the cutting edge AI agents developed by our exceptional team of Machine Learning and Neuroscience research scientists. Your responsibilities will include everything from creating systems for agent testing using 2D and 3D games to developing test problems within physics simulators. You will create graphical visualization of results, build competitive agent leaderboards and test new algorithms on robots. To succeed in this role you will need to have a strong foundation in software engineering and enjoy working on a wide range of challenging problems within a mission-driven team.

As a part of this team, you will aim at automating the design of hardware accelerators for machine learning, covering the design space of TPUs as well as future and emerging, even more specialized inference accelerators. In this role, the benefits are twofold, including a dramatic increase in the productivity of hardware engineers, and aiming for performance levels beyond what is typically achievable by human experts.

As an applied research and development project, the main impact is expected to be internal, through our collaborations with product teams across the Alphabet. When appropriate, open source contributions and academic publications will also be considered.

Artificial intelligence will be one of humanity’s most transformative inventions. At Google 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 diverse learning opportunities and varied career pathways for those driven to achieve exceptional results through collective effort. Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

About the job

At Google DeepMind our mission is to build the world's first general-purpose learning agent. Central to this mission is the complex task of measuring the intelligence of our prototypes. As a Software Engineer, you will be working with the cutting edge AI agents developed by our exceptional team of Machine Learning and Neuroscience research scientists. Your responsibilities will include everything from creating systems for agent testing using 2D and 3D games to developing test problems within physics simulators. You will create graphical visualization of results, build competitive agent leaderboards and test new algorithms on robots. To succeed in this role you will need to have a strong foundation in software engineering and enjoy working on a wide range of challenging problems within a mission-driven team.

As a part of this team, you will aim at automating the design of hardware accelerators for machine learning, covering the design space of TPUs as well as future and emerging, even more specialized inference accelerators. In this role, the benefits are twofold, including a dramatic increase in the productivity of hardware engineers, and aiming for performance levels beyond what is typically achievable by human experts.

As an applied research and development project, the main impact is expected to be internal, through our collaborations with pro