Etched
Kernel Driver Software Engineer
About this role
Etched is seeking a Kernel Driver Software Engineer to design and optimize kernel-mode drivers for custom AI inference accelerators. You'll collaborate with hardware engineers on ASIC co-design, implement advanced virtualization and memory management, and ensure high performance and security for demanding machine learning workloads.
What you'll do
- Design and maintain kernel-mode drivers with focus on reliability, debugging, and performance optimization
- Optimize driver performance for AI workloads, minimizing latency and maximizing throughput
- Implement virtualization support including SR-IOV, VFIO, and para-virtualization technologies
- Design efficient memory management with kernel mapping, page tables, NUMA awareness, and IOMMU configuration
- Build security features for host isolation, memory protection, and device attestation
- Diagnose complex driver issues using kernel debugging tools like ftrace and kgdb
What they're looking for
- C/C++ proficiency
- Kernel-mode driver development and debugging
- Linux operating system internals
- PCIe and hardware interface protocols
- Memory management and synchronization in kernel environments
- Device virtualization technologies (SR-IOV, VFIO)
- Kernel memory mapping, page tables, and IOMMU configuration
- Hardware-software co-design principles
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Etched
Etched builds AI inference hardware, designing and manufacturing complex mechanical and electrical components for data center systems. The company is hiring mechanical engineers, PCB designers, hardware verification engineers, and software engineers to develop manufacturing processes, circuit boards, verification infrastructure, and internal tools across its hardware and operations.
- Website
- etched.com
Likely interview questions
- Walk us through your experience developing kernel-mode drivers. What was the most complex driver issue you debugged, and what tools did you use?
- Describe your experience with memory management in kernel environments—specifically page tables, IOMMU configuration, and NUMA awareness. How have you optimized these for high-bandwidth data transfers?