Efficient Computer
Senior Staff Software Engineer, Linux Runtime & Drivers
$220K–$270K
San Francisco, Bay Area OR Pittsburgh, PA +3 · Senior Staff · Full-time · Posted Oct 6, 2026
- Location
- San Francisco, Bay Area OR Pittsburgh, PA
Pittsburgh, PA
San Francisco, California, United States
San Jose, CA - Experience
- 7+ years of systems software experience.
- Education
- B.S. in Electrical/Computer Engineering, Computer Science, or equivalent; M.S. a plus.
About the job
Owns the Linux user-mode runtime and driver interfaces that connect the compiler, kernel driver, and Fabric accelerator, and leads runtime bring-up and validation.
What you'll do
- Design and maintain the user-mode runtime driver, library, and interfaces for the Fabric ABI and kernel-mode driver.
- Develop runtime support for third-party ML framework backends and lead first-silicon bring-up.
- Establish API, emulation, performance, and hardware-in-the-loop test coverage.
What they ask for
- B.S. in Electrical/Computer Engineering, Computer Science, or equivalent.
- 7+ years of systems software experience, including significant hands-on Linux user-mode driver and language runtime library development for accelerators.
- Production accelerator runtime stack experience, plus experience with accelerator memory models, runtime APIs, compiler interfaces, and kernel/user-space interfaces.
- Pre-silicon simulation, emulation, or QEMU experience; expert C and C++, strong Python, and working knowledge of ARM/AArch64 Linux.
Nice to have
- M.S.; experience with CUDA Runtime (cudart), ROCm, Tenstorrent runtime (TT-Metalium), oneAPI Level Zero, OpenCL, or another accelerator runtime.
- Familiarity with LLVM or MLIR, novel compute architectures, first-generation silicon products, or FPGA prototyping and hardware emulation platforms.
Pay
USD $220,000 to $270,000 base salary; 10% annual bonus (no amount stated).
Tools
Linux, QEMU, PyTorch, ONNX, TensorFlow, C, C++, Python
AI focus
Supports an energy-efficient general-purpose processor for AI and develops runtime interfaces for ML framework backends; use AI-assisted development tools for code, analysis, and debugging.
Model-written summary · the original posting is authoritative