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Snapshot
The role sits within Google DeepMind’s Compute Planning team. The team is responsible for building and managing Google DeepMind’s extensive Machine Learning (ML) Hardware portfolio
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
As a Technical Program Manager in the Compute Planning team you will play a key role in the building and ongoing management of Google DeepMind’s extensive ML Hardware portfolio.
You will work alongside our Product Managers, Engineers and Researchers to help define and optimise DeepMind's overall capabilities in this space.
Key Responsibilities.
- Creating and scaling processes for collecting data on future ML hardware requirements, including next-gen ML accelerators and cloud infrastructure.
- Partnering with portfolio managers and data analysts to allocate capacity across projects effectively and in line with company priorities.
- Providing best practices to researchers and engineers in areas such as resource availability, efficiency, scaling & performance.
- Producing regular targeted communications to leadership, research and engineering teams
- Assisting with new ML hardware/software pilot programs.
- Developing and maintaining tooling (eg: dashboards, automation).
- Producing user guides, process documentation, and other forms of educational resources.
- Troubleshooting compute-related errors in various infrastructure platforms, in partnership with engineering teams.
About you
In order to set you up for success as a Technical Program Manager at Google DeepMind, we look for the following skills and experience:
- Excellent technical understanding and communication ability, with the ability to distil sophisticated technical ideas to their essence
- Skilled at navigating, updating and defining complex processes
- Initiative to solve problems with solutions that are repeatable, scalable and sustainable.
- Proven strong stakeholder management skills
- Comfortable dealing with ambiguity and able to thrive in a dynamic environment.
- A curiosity about Google DeepMind's mission and AI / Machine Learning
- Flexible, adaptable and highly responsive to the needs of the project, team and wider group.
In addition, the following would be an advantage:
- BS degree in Computer Science, Engineering, related fields or equivalent practical technical experience.
- Knowledge of data centre infrastructure and operations.
- Knowledge of cloud infrastructure
If you don’t think you embody all of the above criteria, please still seriously consider applying! This role (and therefore the requirements) is broad, and we’d be excited to discuss how you see yourself contributing across it, in particular the opportunities to learn and grow on the job.
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.
Top Skills
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.
