Advanced Micro Devices, Inc

Sr. Data Center GPU Validation and Debug Engineer

Advanced Micro Devices, Inc$130K — $155K *
Enterprise Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Strong Linux and systems engineering experience, including C/C++, Python, and shell automation.
  • Experience with data center GPUs or high-performance systems.
  • Understanding of GPU architecture, memory hierarchy, and parallel execution.
  • Experience debugging across software, firmware, kernel, and hardware boundaries.
  • Ability to analyze logs, traces, hardware telemetry, and performance counters.

Responsibilities

  • Debug GPU failures across the software and hardware stack including memory faults and performance regressions.
  • Reproduce failures and create actionable test cases.
  • Triage system-level interactions across GPU, CPU, and memory.
  • Validate AI, HPC, and communication workloads on GPU platforms.
  • Characterize performance and identify bottlenecks in compute, memory, and communication.
  • Analyze single- and multi-GPU behavior under varying conditions.
  • Establish benchmarks and automated diagnostics for performance testing.

Benefits

  • Comprehensive health coverage including medical, dental, and vision.
  • Retirement savings plan with employer contributions.
  • Employee stock purchase program.
  • Paid time off and paid holidays.
  • Wellness programs and resources to support employee health.
Full Job Description
THE ROLE

We are seeking an experienced engineer to validate and debug data center GPU products across the complete software and hardware stack, spanning workload behavior and performance qualification as well as platform health and root-cause isolation. The role demands strong technical judgment, disciplined failure isolation, and the ability to trace unexpected behavior from application to hardware, working across firmware, kernel, compiler, library, and framework teams to drive issues to resolution.

KEY RESPONSIBILITIES:
  • Debug GPU failures including hangs, crashes, memory faults, firmware errors, and performance regressions across the full software and hardware stack.
  • Reproduce failures and reduce them to minimal, actionable test cases.
  • Triage system-level interactions across GPU, CPU, memory, networking, power, and platform topology.
  • Validate AI, HPC, and communication workloads across GPU platforms, firmware, and software releases.
  • Characterize performance and identify compute, memory, and communication bottlenecks.
  • Analyze single- and multi-GPU behavior across workload configurations, topology, NUMA, power, and thermal conditions.
  • Establish benchmarks, baselines, and regression-detection methods; correlate microbenchmark results with real workload behavior.
  • Build automated diagnostics, stress tests, performance suites, and regression infrastructure.
  • Support customer-representative validation and escalation reproduction.

REQUIRED QUALIFICATIONS:
  • Strong Linux and systems-engineering experience, with C/C++, Python, and shell automation.
  • Experience with data center GPUs, accelerators, or comparable high-performance systems.
  • Understanding of GPU architecture, memory hierarchy, parallel execution, communication, and synchronization.
  • Experience debugging across software, firmware, kernel, and hardware boundaries.
  • Ability to analyze logs, traces, hardware telemetry, and performance counters.

PREFERRED EXPERIENCE:
  • Strong knowledge of Linux kernel drivers, PCIe, firmware interaction, and memory management.
  • Familiarity with GPU programming models and runtimes such as ROCm/HIP, RCCL, or CUDA equivalents.
  • Experience with AI training or inference frameworks such as PyTorch, vLLM, or SGLang.
  • Experience benchmarking AI inference, training, or HPC workloads, including roofline analysis and model-level profiling.
  • Experience with profiling tools, statistical analysis, and regression detection.
  • Familiarity with multi-GPU topology, PCIe/fabric interconnects, NUMA, GPU firmware, RAS, and rack-scale platforms.
  • Experience with system bring-up, qualification, or production data center operations.
  • Familiarity with CI systems, automated validation infrastructure, and fleet-scale testing.

ACADEMIC CREDENTIALS:
  • Bachelor's or Master's degree in Computer Science, Computer Engineering, Electrical Engineering, or equivalent


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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