Embedded Machine Learning Research Intern
Embedded Machine Learning Research Intern - Audio2Audio and Speech Recognition
Job Description:
We seek a skilled Embedded Machine Learning intern with experience in audio2audio and speech recognition models. In this role, you will be helping with designing and implementing machine learning models for our cutting-edge edge devices and mobile applications.
Responsibilities:
- Help with designing and implementing machine learning models for audio2audio and speech recognition on edge devices and mobile applications
- Optimize machine learning models for performance, accuracy, and memory footprint.
- Work closely with software and hardware engineers to integrate machine learning models into our products
- Conduct experiments to test and validate the performance of the ML models
- Research and stay up-to-date with the latest ML techniques and algorithms
- Present findings and provide recommendations to the team and management
- Develop and maintain documentation of machine learning models and processes
- Collaborate with cross-functional teams to deliver high-quality products
Required Qualifications:
- BSc in Computer Science, Electrical Engineering, or a related field
- Experience with embedding machine learning models on edge devices and mobile applications
- Proficiency in Python
- Proficiency with machine learning frameworks such as TensorFlow, JAX, or PyTorch
- Excellent problem-solving skills and attention to detail
Preferred Qualifications:
- MSc in Computer Science, Electrical Engineering, or a related field
- Experience with Tensorflow Lite and PyTorch Mobile
- Experience with deploying ML models within iOS and Android applications
- 2+ years of experience in machine learning with a focus on audio2audio and speech recognition
- Strong background in signal processing and digital audio theory
- Strong portfolio of relevant projects demonstrating your expertise in audio2audio and speech recognition
- Publications in reputable ML/Speech conferences such as NeurIPS, AAAI, Interspeech, ICASSP, EMNLP, ASRU
- Familiarity with modern chips for Hearables, such as Snapdragon Wear, Greenwaves GAP9, etc.
This is an exciting opportunity to work on cutting-edge products with a highly skilled team of engineers. If you have a passion for machine learning and are experienced with audio2audio and speech recognition, we encourage you to apply. Please include your portfolio of relevant projects and any optional requirements you meet with your application.