Drimva

Google

Staff Software Engineer, GPU Embedded Systems

Sunnyvale, CA, USA · Staff · Full-time · Posted Oct 8, 2026

Experience
8 years in software development; 5 years testing and launching software products; 5 years working with embedded operating systems; 3 years in software design and architecture. Preferred: 8 years with data structures and algorithms; 3 years in technical leadership; 3 years in a complex, matrixed organization.
Education
Bachelor's degree or equivalent practical experience.

About the job

Leads design and development of GPU host systems and virtualization software for large-scale AI/ML infrastructure, from architecture through production deployment.

What you'll do

  • Design and develop GPU accelerator systems and optimize hardware and software for data plane workloads.
  • Develop features, telemetry, and control software for bare-metal, virtualized, and container-based environments; integrate hardware security features.
  • Set the GPU roadmap and architecture with product teams, vendors, and standards committees; adapt systems to software and hardware changes.

What they ask for

  • Bachelor's degree or equivalent practical experience.
  • 8 years of experience in software development.
  • 5 years of experience testing and launching software products, and 5 years working with embedded operating systems.
  • 3 years of experience with software design and architecture; experience with system development, device drivers, and Kernel programming.

Nice to have

  • Master’s degree or PhD in Engineering, Computer Science, or a related technical field; 8 years of experience with data structures and algorithms.
  • 3 years in a technical leadership role and 3 years in a complex, matrixed organization; experience with PCI express, GPU programming, Linux internals, Linux Kernel, Virtualization, C or C+.

Pay

$207000 - $300000 (USD) base salary

Tools

PCI express, GPU, Linux internals, Linux Kernel, Virtualization, C, C+

AI focus

Develops GPU infrastructure and systems supporting large-scale internal AI/ML infrastructure.

Model-written summary · the original posting is authoritative

First seen Oct 21, 2026 · Last verified Nov 4, 2026 (UTC)