AI Systems Performance & Benchmarking Engineer

AMD; Austin (TX); Hybrid; USD 120,000 - 180,000; Full time

Job summary

AMD is seeking an AI Systems Power and Performance Engineer to evaluate and optimize AI workloads on embedded and client platforms. You will work at the intersection of AI software and hardware, delivering data-driven insights that influence product development and customer success.

You will collaborate with AI software teams and platform engineers to characterize workloads, identify bottlenecks, and drive continuous performance improvements.

Qualifications

• Strong Linux systems knowledge and command-line proficiency.
• Experience with performance profiling, workload tracing, and system analysis tools.
• Knowledge of AI frameworks and models is a plus.
• Familiarity with hardware-software interactions (CPU/GPU/Memory).

Responsibilities

• Benchmark and characterize AI inference workloads across AMD embedded and client platforms.
• Execute performance, power, and efficiency analysis of AI workloads including LLMs, VLMs, and CV use cases.
• Develop and maintain automated benchmarking environments and performance dashboards.
• Configure and optimize AI workload execution environments using standard frameworks and runtimes.
• Collect, analyze, and interpret system-level performance traces.
• Investigate bottlenecks in compute, memory bandwidth, latency, and resources.
• Collaborate with software, firmware, architecture, and platform teams for optimization.
• Support benchmarking methodologies for competitive analysis and product evaluation.
• Generate data-driven reports and present findings to engineering stakeholders.

Skills

Linux

Profiling

Python

Shell scripting

Automation

Performance analysis

CPU/GPU/Memory

BIOS

Education

Bachelor's or Master's degree in Computer Engineering, Electrical Engineering, or Computer Science

Job description

AMD is seeking an AI Systems Power and Performance Engineer to evaluate and optimize AI workloads on embedded and client platforms. You will work at the intersection of AI software and hardware, delivering data-driven insights that influence product development and customer success.

You will collaborate with AI software teams and platform engineers to characterize workloads, identify bottlenecks, and drive continuous performance improvements.