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 transparent technical reports and performance summaries for stakeholders

Required Skills
Robust experience in performance benchmarking and system analysis
Positive 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.

embedded software development,graphics processing unit,robotics,artificial intelligence,benchmarking,python,c++,

📌 Lead Ii Embedded Software Bengaluru
🏢 UST
📍 Bengaluru