Software Engineer, Hardware Design

Sorry, this job was removed at 04:09 p.m. (CST) on Friday, Jun 06, 2025
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Zürich
In-Office
Artificial Intelligence
The Role
Snapshot

We’re looking for engineers who are passionate about building software infrastructure. You will be part of a small team conducting exploratory research and engineering towards designing hardware systems using AI. You will have an opportunity for strong impact. No machine learning experience required. Some knowledge in hardware design (from chips to datacenters) would be a plus, but it is not a requirement.

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

Our team at Google DeepMind explores novel computing infrastructure to support future large-scale research in AI. While our work primarily consists of a software engineering effort, it is also strongly tied to hardware engineering, from chip- to data center-scale systems, and all associated performance evaluation aspects. While expertise in that domain is not a requirement, a strong interest in the topic is expected. Our team also works in close cooperation with the Google DeepMind London infrastructure team which supports AI researchers and engineers, and increasingly with Google teams. Exemplifying a kind and responsible approach, you will empower the success of people around you, and elevate others to succeed.

Key responsibilities:
  • Build a software infrastructure that will be used by GDM AI researchers to automatically create hardware systems using AI
  • Build software infrastructure for the design and performance evaluation of hardware systems from chips to data centers
About You

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

  • SWE interpersonal skills (discuss technical ideas effectively with colleagues, e.g. through whiteboard, design docs, presentations; interact directly with our end users on various channels), the effort being highly collaborative, within the project, and with other teams at Google
  • Experience in C++ and/ or Python
  • Ability to code and an appetite to learn
  • Knowledge (or at least a strong interest) in computing hardware, and performance evaluation would be very appreciated.

Deadline: 6th June 2025

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.

 

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The Company
1,218 Employees
Year Founded: 2010

What We Do

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.

Our long term aim is to solve intelligence, developing more general and capable problem-solving systems, known as artificial general intelligence (AGI).

Guided by safety and ethics, this invention could help society find answers to some of the world’s most pressing and fundamental scientific challenges.

We have a track record of breakthroughs in fundamental AI research, published in journals like Nature, Science, and more.Our programs have learned to diagnose eye diseases as effectively as the world’s top doctors, to save 30% of the energy used to keep data centres cool, and to predict the complex 3D shapes of proteins - which could one day transform how drugs are invented.

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