Senior Systems Software Engineer, Windows and Linux Enablement - DGX Station

at Nvidia

USD 224,000-356,500 per year

SENIOR

✅ On-site

Tech Stack
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AI @ 4 API @ 3 CUDA @ 4 Debugging @ 7 GPU @ 4 Linux @ 7 Machine Learning Microservices NCCL NVLink Performance Optimization @ 4 Profiling @ 4 Python @ 6 TensorRT @ 4

Details

DGX Station is NVIDIA's next-generation personal AI supercomputer, built on the NVIDIA Grace Blackwell GB300 Superchip. It is a deskside workstation designed to provide data-center-class AI capabilities to researchers, developers, and AI engineers.

This hands-on role owns full-stack operating system enablement for DGX Station, with a primary focus on Windows and strong coverage of Linux. The engineer will work across NVIDIA's GPU driver, CUDA, firmware, BMC, and AI software teams, collaborate with Microsoft and ODM/OEM partners, and ensure a polished, production-ready experience across both operating systems.

Responsibilities

Own end-to-end Windows enablement for DGX Station, from initial bring-up through WHQL certification and customer-ready shipping quality.
Drive Linux bring-up and continuous enablement on DGX OS and Ubuntu, including kernel module integration, device tree and ACPI configuration, systemd services, initramfs, and DKMS packaging.
Partner with DGX OS and kernel teams to land platform support upstream and in NVIDIA's distribution.
Enable and validate BIOS/UEFI, BMC, and system-level firmware for Windows and Linux on the Grace Arm and Blackwell GB300 architecture.
Ensure ACPI tables, SMBIOS, Secure Boot, measured boot, power management, and hardware abstraction layers work correctly on both operating systems.
Coordinate GPU, display, and compute driver bring-up and validation on Windows using WDDM and MCDM, and on Linux using open GPU kernel modules and DRM/KMS.
Work with NVIDIA's driver team and Microsoft to resolve compatibility issues, achieve WHQL certification, and ensure driver stability across Windows Update and Linux kernel revisions.
Ensure the CUDA Toolkit, cuDNN, TensorRT, NCCL, and NVIDIA AI SDK stack function correctly on DGX Station under Windows and Linux.
Validate AI and deep-learning workload performance, including training, fine-tuning, and inference, and resolve platform gaps on the Arm and GB300 architecture.
Validate NVIDIA AI applications, including NIM microservices, NemoClaw, AI Workbench, and developer tools.
Define and implement test plans covering single-user and multi-user scenarios, container runtimes, application installation flows, and developer workflows.
Drive functional, stress, power, thermal, sleep/resume, S-state cycle, Windows Update, Linux kernel-upgrade compatibility, and long-duration reliability testing.
Own bug triage and resolution across firmware, BMC, driver, and operating system layers.
Serve as the primary technical interface with Microsoft and ODM/OEM partners, coordinating schedules and resolving cross-company technical blockers.
Profile and optimize boot time, GPU compute throughput, NVLink-C2C and memory bandwidth utilization, power efficiency, and thermal behavior.
Create and maintain bring-up guides, known-issue documentation, driver compatibility matrices, recovery and re-imaging procedures, and developer setup instructions.
Enable field and support teams for customer deployments.

Requirements

Bachelor's or master's degree in Computer Science, Electrical Engineering, or a related field, or equivalent experience.
12 or more years of confirmed experience in systems software engineering, with deep expertise in Windows platform enablement, driver development, or operating system integration, along with hands-on experience bringing up Linux on new hardware platforms.
Strong hands-on experience with Windows internals, including kernel-mode drivers, ACPI, power management, Secure Boot, UEFI, WDM/WDF driver frameworks, and the WHQL certification process.
Solid understanding of Linux platform enablement, including kernel modules, device tree and ACPI on Arm, systemd, initramfs, DKMS, and packaging for Ubuntu or DGX OS.
Experience with GPU, display, or compute driver stacks on Windows and/or Linux.
Familiarity with DirectX, WDDM, DRM/KMS, and GPU compute APIs is a strong plus.
Experience enabling hardware platforms, including bring-up, driver integration, validation, and certification for shipping products on Windows and Linux.
Strong debugging and root-cause analysis skills across firmware, driver, and operating system boundaries.
Experience with WinDbg, kernel debugging using kd or kgdb/crash, crash dump analysis, ftrace/ETW, and performance profiling tools.
Ability to coordinate across GPU driver, CUDA, firmware, BMC, and AI software teams, as well as external partners such as Microsoft and ODM/OEMs.
Proficiency in C/C++ and Python.
Experience with Arm architecture is a plus.

Preferred Qualifications

Experience with Windows on Arm platforms, including driver enablement, performance optimization, or application compatibility.
Hands-on experience with CUDA, TensorRT, or AI/ML frameworks on Windows and Linux, especially on Arm and NVIDIA GPU systems.
Experience working with OEM/ODM partners or silicon vendors on Windows and Linux platform certification for workstation- or server-class hardware.
Track record of shipping workstation or server hardware products from bring-up through general availability with Windows and Linux support.
Experience with BMC, Redfish, out-of-band management, or platform manageability software on high-end workstations or servers.
Experience with GPU-accelerated applications, including AI training and inference, content creation tools, or scientific computing.