Master's or PhD degree or equivalent experience in Computer Science, Computer Engineering, Applied Math, or a related field
Required Previous Experiences
At least 2 years of experience reading and debugging performance-oriented code
Experience with performance analysis workflows, including profiling, measurement methodology, reproducibility, and regression triage
Preferred Qualifications
Experience with high-performance kernels or math libraries such as GEMM, attention, or CUTLASS-like concepts
GPU programming or performance experience with CUDA or equivalent parallel programming
Strong understanding of machine learning and deep learning workloads, including training and inference shapes, precision modes, and performance bottlenecks
Familiarity with simulators, analytical modeling, or performance characterization methodology