Skip to content
← MatX

System Software Engineer, Linux Kernel and Device Drivers

MatX · Mountain View

CHECKED 7H AGO

Infrastructureremotesenior
Apply on the lab’s site ↗

At a glance

Highlights

  • Own host software that brings new AI accelerator silicon from prototype to life.
  • Debug first silicon side-by-side with hardware and firmware teams on novel chips.
  • Feed software lessons back into next-generation AI chip architecture decisions.

What they offer

  • 100% paid daily commute via company Uber account or train reimbursement
  • $50/mo flexible perk allowance
  • $35/mo cell and $40/mo wifi reimbursement
  • Up to $1000 home office setup via Amazon business account
  • 100% paid mental health benefit via SpringHealth and Guardian EAP
  • Up to 12 weeks paid parental leave plus 10 weeks pregnancy disability leave

Ideal candidate

Self-driven systems builder with 8+ years bringing chips to life who loves owning hardware-adjacent software from blank page to bring-up and thrives debugging ambiguous cross-stack problems with minimal hand-holding.

Requirements

  • BS or higher in Computer Science, Electrical Engineering or equivalent with 8+ years in low-level systems software
  • Strong hands-on Linux kernel development with shipped device drivers, ideally for PCIe devices
  • Strong C programming in userspace and kernel space
  • Able to program a device from hardware datasheets and register definitions
  • Deep understanding of computer architecture and OS internals including MMIO, DMA, interrupts, IOMMU and virtual memory
  • Experienced debugging complex hardware/software interaction with limited visibility
  • Self-driven and comfortable owning components from blank page through bring-up on a small team

Lab profile

About MatX

Designs vertically integrated AI silicon and systems to run frontier models at physics-limit efficiency.

What they build

  • AI accelerator silicon for GenAI training and inference
  • Rack-scale AI data center systems
  • Full-stack silicon-to-software platform for large ML workloads

Known for

  • Vertically integrated silicon-to-systems design
  • AI accelerator architecture and performance modeling for LLMs
  • High-efficiency power architecture from chip to rack
  • Silicon verification and software-hardware co-verification
More about MatX →
Apply on the lab’s site ↗