About the Team
We are a systems software team building the foundational software for large-scale compute platforms.
We work at the hardware/software boundary across the Linux kernel, accelerators, storage, firmware, and platform validation.
We value rigorous engineering, clear interfaces, measurable performance and reliability, and upstream collaboration where appropriate.
The team partners closely with hardware, architecture, product, validation, and production engineering groups to move new capabilities from design through dependable deployment.
About the Role
You will lead the technical strategy and cross-functional delivery of the low-level GPU software stack for data-center computing.
You will connect accelerator architecture, firmware, kernel drivers, runtimes, communication, telemetry, and fleet reliability into a coherent roadmap.
This is a hands-on individual-contributor role: you will make architecture decisions, guide engineers, review critical implementations, and resolve system-level issues without assuming hiring or performance-management responsibilities.
Responsibilities
- Define the architecture and multi-year technical roadmap for GPU system software across driver, runtime, firmware-interface, management, observability, and reliability layers.
- Set priorities and technical standards for accelerator enablement, balancing near-term product commitments with compatibility, performance, serviceability, and long-term maintenance.
- Own end-to-end integration from architecture and pre-silicon planning through bring-up, qualification, general availability, fleet monitoring, and sustained operation.
- Lead cross-functional execution among silicon, firmware, kernel, compiler, library, machine-learning framework, server, network, storage, validation, and production teams.
- Resolve ambiguous system-level tradeoffs involving APIs, resource management, memory and interconnect topology, telemetry, recovery, security, and workload performance.
- Remain technically involved through prototypes, critical-path code and design reviews, performance analysis, and leadership during high-severity failure investigations.
- Define measurable release and reliability criteria, including qualification coverage, regression thresholds, fault containment, automated repair, and fleet-health indicators.
- Mentor engineers, raise the quality of architecture and debugging practices, and communicate technical decisions to both specialist and executive audiences.