Member of Technical Staff - Inference Optimization

Required Qualifications

• Deep Kernel Authorship You have written production CUDA or ROCm kernels from scratch. You understand warp execution, shared memory bank conflicts, occupancy, and instruction-level parallelism at an intuitive level. Strong proficiency in C++11 or higher, CUDA, Triton, and ideally LLVM/MLIR.
• Hardware Architecture Knowledge Strong familiarity with NVIDIA Hopper/Ampere and AMD CDNA architectures. You know the differences between HBM bandwidth profiles, cache sizes, and execution units and you write code that reflects that knowledge. Deep understanding of memory layout, vectorization, thread and block scheduling, and cache behavior.
• Precision & Numerical Fluency Solid grasp of numerical stability, mixed precision arithmetic, and modern precision formats. Experience making principled trade-offs between precision and performance in production systems.
• Profiling Fluency Comfortable with Nsight Compute, rocprof, Perfetto, VTune, and roofline modeling. You do not guess where the bottleneck is. You measure it.
• Parallel Programming Breadth Strong background across parallel programming models including CUDA, Triton, SYCL, OpenCL, or OpenMP. Experience optimizing irregular algorithms such as sparse linear algebra or graph computations.
• Systems Thinking Ability to reason about how individual kernels compose into larger execution graphs, and how kernel-level decisions propagate up through the inference or training stack.
• Great Team Spirit A mission-driven approach to engineering, valuing clear communication, hands-on execution, and collective success over individual silos