Advanced Micro Devices, Inc

Principal System Software Architect, AI/GPU Platforms

Advanced Micro Devices, Inc$160K — $190K *
Enterprise Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 5-7 years of experience in x86 computing architecture and Linux systems software
  • Demonstrated record in influencing industry standards and open-source contributions
  • Strong skills in technical leadership and architectural judgment
  • Experience with cross-functional team collaboration across hardware and software
  • Advanced C programming abilities, particularly for kernel and system software

Responsibilities

  • Define and oversee system software and platform architecture for Linux and virtualization
  • Drive long-term architectural roadmaps for x86-based platforms
  • Lead design reviews across various systems layers
  • Architect and prototype Linux kernel and device drivers
  • Provide leadership for system performance and reliability
  • Conduct root-cause analysis across application and hardware layers
  • Engage with open-source communities and external software partners

Benefits

  • Comprehensive health insurance plans
  • 401(k) retirement savings plan with company match
  • Paid time off (PTO) and holidays
  • Flexible work options positioned for work-life balance
  • Employee resource groups focused on various interests and backgrounds
Full Job Description
THE ROLE

You will join the system software architecture team behind AMD Instinct™ accelerators, the GPUs powering some of the world's largest AI and HPC deployments. This role is focused on next-generation, rack-scale AI platforms in the MI400 class spanning the GPU, the node, and the scale-up/scale-out fabric that binds thousands of accelerators into a single training and inference system.

THE PERSON

As a Systems Software Architect, you sit at the intersection of silicon, firmware, driver, runtime, and framework. You define how the software stack exposes and orchestrates the hardware so that AMD's largest customers can extract maximum performance, reliability, and utilization from their infrastructure.

KEY RESPONSIBILITIES
  • Own the end-to-end system software architecture for one or more MI400-class subsystems for example GPU memory management, scheduling and queuing, RAS and serviceability, virtualization/partitioning (SR-IOV), or the scale-up/scale-out interconnect software model.
  • Drive architecture across the stack: kernel-mode driver (amdgpu/KFD), user-mode runtime (ROCr/HSA), firmware interfaces, and the ROCm software platform, ensuring the layers compose cleanly and perform.
  • Partner with silicon and SoC architects during pre-silicon definition to shape hardware/software interfaces, programming models, and register/firmware contracts before tape-out.
  • Define the software strategy for multi-GPU and rack-scale topologies, including Infinity Fabric / UALink-style interconnect, collective communication (RCCL), memory coherence, and address translation across the platform.
  • Establish architecture for reliability, availability, and serviceability at scale, error detection, containment, telemetry, recovery, and graceful degradation across large clusters.
  • Set direction on performance: identify bottlenecks in the launch path, memory subsystem, and communication path, and define the software mechanisms to close them.
  • Produce architecture specifications, reference designs, and design reviews that align firmware, driver, runtime, and framework teams onto a shared plan.
  • Act as a technical anchor across AMD and with strategic hyperscale and AI customers - translating their workload requirements into architectural direction and representing AMD in deep technical engagements.

PREFERRED EXPERIENCE
  • Linux Memory Management and Heterogeneous Memory Management (HMM).
  • GPU / DRM driver development.
  • Cache coherence and memory consistency protocols.
  • GPU Networking technologies including including scale up transport, NVLink, UALink, RDMA, and peer-direct.
  • Scale-up and scale-out networking, and communication collectives (e.g., RCCL/NCCL), MPI, or SHMEM.
  • Data-center fabrics such as Infinity Fabric, UALink, Ultra Ethernet, InfiniBand, and RoCE, with topology-aware software.

DESIRABLE EXPERIENCE
  • Direct experience with the ROCm stack, AMD Instinct, CUDA, or comparable GPU compute ecosystems.
  • Hands-on experience developing or optimizing GPU compute kernels (HIP, CUDA, Triton, or assembly-level tuning).
  • Experience with deep learning frameworks like PyTorch and TensorFlow in particular including framework integration, custom operators, and performance tuning on GPU backends.
  • Familiarity with the broader ML framework and compiler ecosystem (PyTorch, JAX, TensorFlow, ONNX, MLIR/compiler stacks).
  • Hands-on experience with GPU compute technologies such as OpenCL and Vulkan.
  • Familiarity with AI/ML training and inference workloads (transformers, large-scale distributed training, KV-cache and memory pressure, inference serving).
  • Background in virtualization, multi-tenancy, confidential computing, or cloud GPU provisioning.
  • Contributions to open-source kernel, driver, or runtime projects.


ACADEMIC CREDENTIALS:
  • Bachelor's or Master's in Electrical Engineer, Computer Engineering, Computer Science, or a closely related field


LOCATION:

Austin, TX

Santa Clara, CA

This role is not eligible for visa sponsorship.

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Benefits offered are described: AMD benefits at a glance.

About Advanced Micro Devices, Inc

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Learn more about Advanced Micro Devices, Inc
Size
15,500 employees
Market Cap
$100.9 billion
Industry
Net Income
$2.4 billion
Founded
1969
5 Year Trend
+30.9%
Revenue
$9.7 billion
NASDAQ

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