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Design systematic evaluation frameworks and benchmark LLM performance
Diagnose ML infrastructure failures with structured root-cause analysis
Design sound experiments and analyze results with statistical rigor
Debug ML infrastructure issues and trace root causes with systematic analysis
Design optimization solutions with rigorous experimental validation
Design statistically valid benchmarks and interpret results
Design and run rigorous benchmarks with statistical validation
Identify bottlenecks, optimize algorithms, validate improvements with rigorous trade-off analysis
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