Lesson 1685 of 2244
AI Hardware Evaluations Engineer: Benchmarking GPUs Beyond MFU
Hardware-eval engineers measure real-world AI performance across H100, B200, MI300X, and Trainium with workload-specific rigor.
Adults & Professionals · Careers & Pathways · ~19 min read
The premise
Hardware evaluations engineers help finance and platform teams pick between Nvidia, AMD, Cerebras, Trainium, and Groq based on real workloads, not vendor decks.
What AI does well here
- Measure model FLOPs utilization (MFU) on real training jobs
- Profile inference latency, throughput, and tokens-per-dollar
- Reproduce vendor benchmarks under your own thermal and network conditions
What AI cannot do
- Predict next-gen vendor performance from current data sheets alone
- Account for software-stack maturity differences month over month
- Override commercial terms that reshape TCO regardless of FLOPs
Key terms in this lesson
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