Staff Software Engineer - Kernel & Performance

Google DeepMind; Mountain View (CA); On-site; USD 207,000 - 300,000; Full time

Job summary

Google DeepMind seeks a Software Engineer to build and test software for a new systolic array accelerator, including developing test problems in physics simulators and creating visualizations of results.

You will collaborate with machine learning and neuroscience teams, implement production-grade performance software, and help establish efficient, scalable tooling and benchmarks in Mountain View, CA.

Qualifications

• Bachelor’s degree or equivalent practical experience.
• 8 years of experience in software development.
• 5 years of experience testing, and launching software products.
• 5 years of experience in power or performance modeling or system performance analysis.
• 5 years of experience with Linux Kernel development and software and hardware architecture.
• 3 years of experience with software design and architecture.

Responsibilities

• Write low-level performance software for a new systolic array accelerators.
• Identify high-value algorithms and problems that are a match to this new machines.
• Use that direct experience delivering production code to build programming infrastructure to ease programming on the new accelerator for the performance software engineers and general software engineers who follow.
• Collaborate with application, algorithm, and performance-tuning experts to codesign solutions for the best efficiency, performance, and programmability.
• Communicate the performance, programmability, and efficiency results to our team and to our partner teams.

Skills

Software development

Testing and launching software

Performance modeling

Linux Kernel development

System architecture

Education

Bachelor’s degree or equivalent practical experience

Job description

Google DeepMind seeks a Software Engineer to build and test software for a new systolic array accelerator, including developing test problems in physics simulators and creating visualizations of results.

You will collaborate with machine learning and neuroscience teams, implement production-grade performance software, and help establish efficient, scalable tooling and benchmarks in Mountain View, CA.