边缘机器学习软件工程师：模型优化 - PICO - 圣何塞

PICO has been at the forefront of the consumer electronic market.

We have teams in Europe, Japan and South Korea.

AR/VR imaging team.

- Profile and analyze model performance and power consumption on simulators, emulators, and silicon platforms.

- Identify bottlenecks related to compute, memory bandwidth, data movement, and scheduling - Apply hardware-aware optimization strategies, such as quantization, compression and operator fusion, to meet latency, memory and power targets.

- Work closely with algorithm, compiler, firmware and hardware teams to debug functional and performance issues.

- Master's degree in Computer Science, Electrical Engineering, Computer Engineering, or a related field, or equivalent practical experience.

- 3+ years of industry experience in machine learning software engineering, model deployment, or ML systems for production environments.

- Strong understanding of deep learning architectures, including CNNs and Transformers.

- Knowledge of ML accelerators' architectures, operator fusion, memory hierarchies, and data movements.

- Practical experience with popular ML frameworks, like PyTorch / TensorFlow.

- 5+ years of industry experience in machine learning software engineering, model deployment, or ML systems for production environments.

- Understanding of model inference constraints on edge devices, including latency, power, and accuracy trade-offs and optimization techniques.

- Understanding of quantization techniques, such as PTQ and QAT.