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X Applicants in San Francisco: Qualified applications with arrest or conviction records will be considered for employment in accordance with the San Francisco Fair Chance Ordinance for Employers and the California Fair Chance Act.Note: By applying to this position you will have an opportunity to share your preferred working location from the following:
Mountain View, CA, USA; San Francisco, CA, USA.
Minimum qualifications: - Bachelor's degree in Computer Science, a related technical field, or equivalent practical experience.
- Experience in software development using Python and C .
- Experience with machine learning (ML) hardware accelerators, ML compiler stacks (e.g., JAX, PyTorch, XLA), and kernel development.
Preferred qualifications: - PhD degree in Computer Engineering, Computer Science, or a related field.
- 2 years of experience with full-stack system development for hardware accelerators.
- 2 years of experience with collaborative, hyper-scalar software development and engineering best practices.
- Experience scoping, planning, and executing projects towards team goals in ambiguous environments.
About the jobWe are building a next-generation compute platform for AI inference workloads, with an emphasis on memory technologies, Hardware (HW) acceleration, and Software (SW)/HW codesign.
We are looking for enthusiastic engineers to join the project.
This is a coding role for engineers who like to take initiative and get things done, with a focus on ML compiler stack and inference infrastructure.
At DeepMind you will be joining our team of scientists and engineers who are directly impacting the future of machine learning for Google and industry.
US: $174000 - $252000 (USD) 15% bonus target equity benefits
Learn more about benefits at Google .
Responsibilities - Direct full-stack Software (SW) role, focusing on ML compiler and inference infrastructure.
- Design and develop ML compiler stack to bridge AI workloads and low-level Hardware (HW) operators.
- Design and develop SW infrastructure to enable high performance inference.
- Drive SW/HW codesign, kernel optimization, performance tuning, and debugging.
