Software Engineer - Performance Tools
$200,000–$240,000 year
On-site · San Jose, California, United States
Job Summary
Design and develop a sophisticated performance analysis tool for a cutting-edge ML accelerator. Key responsibilities include leading the architecture and design of performance analysis software, developing methods for low-level data collection, and implementing system tracing and synchronization techniques. The role requires strong proficiency in C++ or Rust, a solid understanding of computer architecture, and experience in performance analysis tools. Collaboration with hardware architects and ML engineers is essential to define requirements and develop effective visualizations for performance data.
Required Qualifications
- Strong proficiency in C++ or Rust
- Proficiency in Python is a plus
- Deep understanding of computer architecture (CPU, GPU, accelerators), memory hierarchies (caches, DRAM), and interconnects (especially PCIe).
- Proven experience in low-level performance analysis, profiling, and bottleneck identification on complex hardware systems (GPUs, CPUs, FPGAs, or custom ASICs).
- Experience with performance analysis tools (e.g., NVIDIA Nsight, AMD uProf, Intel VTune, perf, Tracy, ETW).
- Experience working close to hardware, potentially reading performance counters or interacting directly with device drivers.
Desired Qualifications
- Direct experience developing performance analysis or debugging tools.
- Experience with ML accelerator architectures (GPUs, TPUs, etc.).
- Experience with kernel-mode driver development (Linux or Windows).
- Understanding of compiler internals, code generation, and optimization.
- In-depth knowledge of the PCIe protocol and analysis tools (PCIe analyzers).
- Experience with multi-chip or multi-host accelerator systems (e.g., TPU pods, or NVidia DGX clusters)
- Experience with firmware or embedded systems development.
- Experience with hardware description languages (Verilog, VHDL) or hardware verification.
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