AI Benchmarking & Performance Engineer

Overview:
We are looking for an experienced AI Benchmarking Performance Engineer to measure, analyze, and optimize AI model performance across modern computing platforms (CPU, GPU, and NPU). This role focuses on real-world AI workloads including vision, speech, and robotics models.

Key Responsibilities:
Benchmark AI models such as Open VLA, YOLOv8, Whisper, Pi Droid, Groot, and ML Perf 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 (Py Torch, 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, V Tune, Nsight or similar
Programming proficiency in C/C++, Python/Perl.

Preferred Skills:
Experience with robotics or edge AI pipelines
Experience with simulation environments or real-world deployment