Neuronetwork System Engineer

TetraMem is seeking a Neuronetwork System Engineer to develop and deploy lightweight machine learning models for edge AI applications, particularly audio processing. The role focuses on optimizing models for embedded platforms, integrating them into production systems, advancing inference efficiency, and providing technical leadership and mentorship.

Responsibilities:

• Develop, optimize, and deploy lightweight machine learning models for edge AI applications, particularly for audio processing
• Implement and optimize ML models on embedded platforms, including FPGA and custom ASIC solutions
• Work closely with hardware and software teams to integrate ML models into production systems
• Research and implement state-of-the-art ML techniques to enhance model efficiency, latency, and power consumption for embedded AI applications
• Improve inference efficiency and model compression techniques, including quantization, pruning, and knowledge distillation
• Collaborate with cross-functional teams to drive innovation and contribute to the overall system architecture
• Provide technical leadership and mentorship to junior engineers
• Publish research findings, present at conferences, and contribute to open-source projects when applicable