Edge ML Software Engineer: Model Optimization- PICO- San Jose

As a world-renowned VR/AR brand with independent innovation and R&D capabilities, PICO has been at the forefront of the consumer electronic market. We have teams in Europe, Japan and South Korea. Now we are looking for experts in image pipeline to join us to build our AR/VR imaging team.

Responsibilities:

• Convert and compile ML models for execution on edge NPUs, and apply quantization mechanisms.
• 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.

Requirements:

• Minimum Qualifications

• 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 Py Torch / Tensor Flow.

• Proficiency in Python and C/C++

• Preferred Qualifications

• 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.