Software Engineer, Machine Learning and Electronic Design Automation GenAI - Mountain View, CA

Snapshot

We are looking for engineers who understand that the end of Moore’s Law will require a revolution in chip design methodology (EDA). Our work emphasizes three opportunities for novel approaches to EDA: cloud/hyperscale computing--which allows algorithms to operate totally differently; machine learning--which provides dramatic automation opportunities; and integration--since we can now co-design and/or co-optimize algorithms, compilers, and hardware. 

This is a hands-on coding role for engineers who like to roll up their sleeves and get things done. At Google DeepMind you’ll be joining our team of scientists and engineers who are directly impacting the machinery of machine learning.

The Role

You should be passionate about making digital electronic design better, including (but not limited to) how to use machine learning, cloud computing, and/or co-design to dramatically improve EDA:

• Skilled at rapid yet rigorous prototyping and software tool building for design automation; aptitude to quickly determine whether an approach is worth following or not without spending too much time.


• Excited to invent, prototype, and deliver tools employing novel optimization techniques and machine learning to re-invent AI chip design, from RTL to GDSii.

Existing team members are self-driven and motivated, bring passion to their work, are comfortable working in a highly ambiguous environment, are open and curious to seek out and learn new perspectives, can challenge their own thinking, and are excellent and direct communicators and collaborators. 

About You

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

• Experience advancing EDA, including using any one or more of machine learning, cloud computing, or HW/SW co-design to improve EDA outcomes.


• Demonstrated ability to innovate. 


• Ability to scope, plan, and execute projects towards team goals. 


• Desire to revolutionize chip design and the flexibility to thrive in a rapidly evolving organization.

In addition, 1-2 years of experience of the following would be helpful:

• Experience with collaborative, hyper-scalar software development and engineering best practices.


• Interest in working with full-stack system development, from HW/SW co-design through implementation (ideally through post-silicon)..


• Interest in JAX, GPU, or other SIMD programming (eg, for ML/AI or scientific computing).


• Ph.D. in Electrical Engineering, Computer Science or related field; or other similar experience.

Note: In the event your application is successful and an offer of employment is made to you, any offer of employment will be conditional on the results of a background check, performed by a third party acting on our behalf. For more information on how we handle your data, please see our Applicant and Candidate Privacy Policy .

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 opportunities 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.