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AMD · 2 days ago

GPU Performance Attainment Engineer - ML and HPC Applications

Orlando, FL

Full-time

Onsite

Mid, Senior Level

$119K/yr - $178K/yr

4+ years exp

AMD is a company focused on building innovative products that enhance computing experiences across various domains, including AI and data centers. The GPU Performance Attainment Engineer will be responsible for optimizing GPU performance for machine learning and high-performance computing applications, collaborating with multiple teams to deliver cutting-edge solutions.

AI InfrastructureArtificial Intelligence (AI)Cloud ComputingComputerEmbedded SystemsGPUHardwareSemiconductor

Growth Opportunities

H1B Sponsor Likely

Hiring Manager

ELIA VALLADARES- SHRM CP

Responsibilities

Debug performance issues and analyze data from the full-chip Emulation Platform, RTL Simulator, and Architecture and Roofline Models

Analyze model projection results and identify algorithm issues to find novel solutions for improving the accuracy of projection for different families of products, and over multiple generations

Get performance projections for kernels using an analytical model. Identify efficiency issues and work with model owners to resolve performance projection shortcomings

Identify technical problems, break them down, summarize multiple possible solutions, and help the team to make progress

Automate processes related to performance infrastructure and data collection tasks, to enhance productivity and refine processes for improved efficiency

Engage with the workloads team to acquire and align on required workloads, run the selected workload traces on the performance simulator, analyze the performance results and metrics to root cause any anomalies

Collaborate with simulator team to bridge gaps between the performance numbers and the performance targets

Influence design trade-offs and optimizations by working closely with compiler, driver, library, and hardware engineers to achieve the highest performance for selected workloads

Innovate new algorithmic improvements that exploit the strengths of the hardware architecture to deliver the best possible machine learning performance

Qualification

GPU performance analysisMachine Learning workloadsPerformance modeling toolsC/C++ programmingScripting PythonScripting PerlScripting ShellGPGPU programming APIsAnalytical skillsCollaborative team environmentCommunication skills

Required

Hands-on expertise in pre-silicon performance analysis, debugging, and optimization of GPU architectures

Strong communication skills with the ability to clearly convey complex technical concepts and influence decisions across multiple organizational levels

Proactive individual eager to push the boundaries of GPU performance for AI and ML workloads through innovative, data-driven solutions

Strategic thinkers with strong analytical skills who thrive in collaborative team environments

Ability to adapt quickly and leverage collective strengths to develop impactful, cutting-edge solutions