Kernel Driver Software Engineer
$150,000–$200,000 year
On-site · San Jose, California, United States
Job Summary
The Kernel Driver Software Engineer will primarily focus on kernel-mode driver development, performance optimization for AI workloads, and hardware integration. Responsibilities include diagnosing and resolving driver-related issues, implementing virtualization support, and ensuring security within kernel drivers. Required qualifications include proficiency in C/C++, experience in developing and debugging kernel-mode drivers, and strong knowledge of memory management and PCIe. Candidates should have excellent collaboration skills and familiarity with debugging tools. Strong candidates may also have experience with GPU drivers and ML workloads. The position offers relocation support and generous benefits.
Required Qualifications
- Proficiency in C/C++
- Strong understanding of kernel-mode driver development and debugging
- Deep understanding of operating system internals (Linux preferred)
- Experience with hardware/software interfacing and device drivers
- Experience with memory management and synchronization in kernel environments
- Strong understanding of PCIe and other hardware interfaces
- Experience with device virtualization technologies, including SR-IOV and VFIO
- Strong understanding of kernel memory mapping, page table configuration, and IOMMU
- Familiarity with hardware-software co-design principles
- Proven ability to analyze complex technical problems and provide effective solutions
- Excellent communication and collaboration skills
- Experience with version control systems (e.g., Git)
- Experience with debugging tools (e.g., gdb, kgdb)
Desired Qualifications
- Experience with GPU driver development
- Experience with CUDA, OpenCL, or other GPU programming models
- Experience with performance profiling and benchmarking tools (perf, VTune)
- Knowledge of hardware virtualization techniques, including para-virtualization
- Experience with CI/CD pipelines
- Experience with Rust
- Experience with ML frameworks like Tensorflow or Pytorch
- Experience with data center orchestration technologies (Kubernetes, Docker)
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