The ideal candidate will have a strong background in applying machine learning to Digital Signal

Processing, particularly in audio signal analysis and accelerometer data analysis. This role involves

developing innovative ML models, including CNNs, RNNs, GANs, and leveraging techniques such as LLMs

and low-rank adaptation for enhancing our product offerings. The successful candidate will also be

proficient in MLOps practices and deploying ML models into production environments.

Key Responsibilities:

1. Custom ML Model Development: Design and build custom machine learning models from

scratch, tailored to specific applications in digital and audio signal processing, and accelerometer

data analysis. The ideal candidate will have published papers or demonstrable customized model

custom built for specific proble...