Job Description

Decades of research have led to tremendous successes in analyzing and understanding the sound patterns generated by humans i.e., speech. These efforts gave us automatic speech recognition, one of the key Artificial Intelligence (AI) technologies today. However, we cannot say the same about the rest of our rich and diverse auditory world, which, obviously goes far beyond speech. With intelligent audio analytics, we envision to “see” the world of things and machines through audio patterns. Our team is developing novel signal processing and machine-learning algorithms for analyzing, detecting, and classifying the audio patterns generated by various physical processes around us.

The intern will part of a dynamic and highly motivated team working on building exciting new products and services enabled by audio signature based understanding of events and/or physical processes. Our core technology aims to leverage recent developments in deep learning and state-of-the-art audio signal processing algorithms. The responsibilities of the intern would include implementing/deploying signal processing and machine learning algorithms on embedded/mobile devices, designing and building working prototypes (including mobile application development) and hands-on experimentation/validation of the technology in practical scenarios. Primary use cases can be focused on physical security, activity/abnormality detection and/or machine condition monitoring from audio signatures. The intern will closely work with our machine learning/audio analytics researchers and integrate novel research ideas into proof-of-concept prototypes. In terms of engineering effort, this will involve iterative design improvements, algorithm fine-tuning and continuous test integration according to use case requirements. In summary, we are looking for a highly motivated engineer with solid hands-on machine learning background seeking to build exciting new technologies in a fast-paced environment.