Linux Kernel Engineer (Memory Management & Device Drivers)

Anagha Techno Soft

San Jose, CA, United States

3 months ago

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Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience level

Expert

Working hours

Regular working hours

Job source

dice.com

Tech stack

Artificial Intelligence C++ (Programming Language) Computer Engineering Data Centers Software Debugging Device Drivers Memory Management Emulators Python (Programming Language) Kernel-Based Virtual Machine Linux Kernel Linux-Powered Devices

+13 more

Open Source Technology PCI Express Performance Tuning Quick EMUlator (QEMU) Reduced Instruction Set Computing System Programming Virtualization Technology JavaScript Pagination Plugin Information Technology Trace32 Restful APIs Grpc Nvme

Job description

Design and optimize Linux kernel memory management (paging, allocation, HugePages, page cache, LRU).
Develop and maintain Linux device drivers for high-speed interfaces such as PCIe (Gen5/6), NVMe, and accelerator hardware.
Work on heterogeneous memory systems, including UVM, memory tiering, and CXL-based memory expansion.
Enable and optimize virtualization environments using KVM and QEMU (IOMMU, interrupt handling, memory virtualization).
Collaborate with hardware teams on SoC bring-up, register definitions, and memory architecture (ARMv9 / RISC-V).
Perform low-level debugging and performance tuning using kernel tracing tools, hardware debuggers (TRACE32), and emulation platforms.
Contribute to system-level architecture and resolve complex performance and memory-related issues.

Requirements

Strong expertise in Linux Kernel Development, especially Memory Management (MM subsystem).
Hands-on experience with device driver development (PCIe, NVMe, or similar high-speed interfaces).
Deep understanding of low-level programming in C/C++ (Assembly is a strong plus).
Solid knowledge of hardware-software interaction, including DMA, cache coherency, and memory subsystems.
Experience with virtualization technologies (KVM, QEMU, IOMMU).
Strong debugging skills in complex, low-level environments., * Experience with CXL (Compute Express Link) or next-gen memory architectures.
Exposure to Python, gRPC, or REST APIs for tooling, automation, or integration.
Familiarity with ARM or RISC-V architectures.
Contributions to mainline Linux kernel or open-source projects.
Knowledge of AI/ML or data center workloads at the system level., * MS/BS in Computer Science, Computer Engineering, or related field.