Kernel Engineering Lead for AI Compute Hardware

MatX

Mountain View (CA)

Hybrid

USD 120,000 - 275,000

Full time

14 days+

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Benefits offered by this job

Equity
Health Insurance
PTO 4 wks
Holidays
Remote work

Job summary

MatX is building the compute platform for AGI and seeks a hands-on TLM to lead the Kernel team in Mountain View. You will mentor engineers, set technical direction, and contribute code implementing high‑performance compute kernels for specialized AI hardware.

You will partner with ML and Hardware teams to maximize output, improve diagnostics, and ensure tight integration of software with hardware. The role combines leadership with hands‑on kernel development across a cutting‑edge stack.

Qualifications

  • 2+ years of engineering team management experience.
  • 7+ years of working within engineering teams.
  • Bachelor of Computer Science or equivalent degree.
  • Experience optimizing software for specialized hardware, employing parallelism and SIMD/assembly optimization or GPU/CUDA programming.
  • Proficient in assembly, C++, C, Zig, or Rust.
  • Ability to navigate ambiguity, manage escalations, and align stakeholders around infra decisions.
  • Excellent communication and collaboration skills, with a track record of translating technical trade-offs.

Responsibilities

  • Manage, mentor, and build a kernel engineering team.
  • Design and optimize kernels interfacing with hardware.
  • Collaborate with ML and Hardware teams to co-design AI architectures.
  • Provide guidance on hardware architecture from a programmer's perspective.

Skills

Team management
Kernel development
C/C++
Rust
Zig
Parallelism/SIMD
Communication

Education

Bachelor of Computer Science or equivalent

Tools

CUDA
GPU programming

Job description

MatX is building the compute platform for AGI and seeks a hands-on TLM to lead the Kernel team in Mountain View. You will mentor engineers, set technical direction, and contribute code implementing high‑performance compute kernels for specialized AI hardware.

You will partner with ML and Hardware teams to maximize output, improve diagnostics, and ensure tight integration of software with hardware. The role combines leadership with hands‑on kernel development across a cutting‑edge stack.

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