About the role
Key Responsibilities
- Benchmark AI models such as OpenVLA, YOLOv8, Whisper, Pi Droid, Groot, and MLPerf Client and similar workloads
- Measure performance metrics including latency, throughput (FPS), memory usage, and power efficiency
- Set up and run repeatable benchmarking pipelines across different hardware platforms
- Perform system-level analysis to identify bottlenecks in CPU, GPU, memory, and data pipelines
- Optimize AI models and pipelines using profiling tools and performance tuning techniques
- Integrate AI models into application pipelines (e.g., robotics or edge AI workflows) and measure end-to-end performance
- Compare performance across platforms (AMD, NVIDIA, Qualcomm, etc.) and generate competitive insights
- Automate benchmark execution, data collection, and reporting
- Prepare clear technical reports and performance summaries for stakeholders
Required Skills
- Strong experience in performance benchmarking and system analysis
- Good understanding of AI/ML models and inference frameworks (PyTorch, ONNX, etc.)
- Experience with Linux systems and performance tools
- Knowledge of CPU/GPU/NPU architectures and memory systems
- Experience with profiling tools such as perf, VTune, Nsight or similar
- Programming proficiency in C/C++, Python/Peral.