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.

 We develop and apply state-of-the-art AI methods and models to Chip Design and work closely with research and product teams across Google.

Our team is composed of research scientists, research engineers and software engineers that have already had a big impact on real products via research breakthroughs. We work on lighting the path of new ideas that can become new products. We work closely with hardware engineers, architects, and ML model developers to generate novel ideas and bring them to  products. 

The mission of our team is to enable “near infinite compute at near zero cost”. This implies working across the entire software and hardware stack to discover opportunities for optimization and create AI based-technologies that improve the efficiency of training and serving AI workloads. We work with, and we optimize EDA tools for better quality of results, performance, and scalability.

At Google DeepMind we've built a unique culture and work environment where long-term ambitious research grounded in real problems can flourish.

As part of our team at Google DeepMind you'll have opportunities to advance AI for Chip Design to enable breakthrough capabilities, and pioneer next-generation products in collaboration with teams spanning major Product Areas.

There are many fundamental research and transformative product landing opportunities, including but not limited to:

• Enable the most advanced ML models and technologies for chip design. 
• Enable research into breakthrough technologies that will have a big impact for Google products and for the whole chip design industry.
• Enable efficiency across the entire AI learning stack.
• Engage and work in a fast paced, rapidly shifting environment, demonstrating flexibility and the ability to bring clarity in ambiguous problem spaces.

• Develop the infrastructure to scale tools for chip design and accelerate the chip design process
• Develop interfaces to connect commercial and open source tools for chip design
• Work with research engineers to build automation for tools, using AI to drive architecture exploration and reduce the search space
• Build dashboards to track improvements in chip design workflows
• Enable efficiency across the entire AI learning stack.

In order to set you up for success as a Software Engineer at Google DeepMind,  we look for the following skills and experience

• B.S./M.S. in Computer Science or related quantitative field with 5+ years of relevant experience.
• Experience in building distributed services, with particular emphasis on utilizing the Google infrastructure
• Experience using testing methodologies:

In addition, the following would be an advantage: 

• Ability to deal with evolving requirements, adapt to change.
• Delivery of high quality software at scale.
• Experience with EDA tools or a strong interest in learning about EDA processes and methodologies.
• Excel at teamwork and cross-team collaborations.

At Google DeepMind, we value diversity of experience, knowledge, backgrounds and perspectives and harness these qualities to create extraordinary impact. We are committed to equal employment opportunity regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, pregnancy, or related condition (including breastfeeding) or any other basis as protected by applicable law. If you have a disability or additional need that requires accommodation, please do not hesitate to let us know.