The XR Audio team at Meta is developing the next generation of speech and audio enhancement algorithms for wearables in various acoustic environments to transform entertainment and social experiences.
Requirements
Research experience in one or more of these areas: machine learning, deep learning, audio/speech processing, ML model compression, or related fields
Experience building novel computational models in audio or speech application domains using machine learning and/or signal processing
Experience with Python/shell scripts/Matlab/C/C++ or similar
Experience working with machine learning libraries such as Pytorch and Tensorflow
Proven track record of publications at ICASSP, Interspeech, WASPAA, IWAENC, IEEE TASLP, Neurips or similar
Demonstrated software engineer experience via an internship, work experience, coding competitions, or widely used contributions in open source repositories (e.g. Github)
Strong background in one or more areas in Digital Signal Processing and Machine Learning such as: 1) Experience with research and development of real-time audio and speech digital signal processing solutions from concept to shipping on resource-limited devices, 2) Experience with developing scalable machine learning models that can evolve with newer device generations with minimal additional data, 3) Experience with techniques for model compression and/or deploying ML models on MIPS/Memory/Power constrained DSP devices, 4) Experience with large scale model training, implementing algorithms, and evaluating performance with objective or subjective audio metrics
Responsibilities
Research, model, design, develop and test novel audio and speech processing algorithms using a combination of machine learning and signal processing to tackle unsolved real-world problems and push the state of the art in audio and advance AR/VR experiences
Lead and contribute to cutting-edge AI model research that leads to publications on top-tier Audio/ML conferences
Independently design and implement algorithms, train advanced AI models on large datasets, and evaluate their performance
Develop novel deep learning techniques, to achieve state-of-the-art accuracy within the constraints of on-device and real-time execution
Collaborate with other research scientists and software engineers to develop innovative deep learning techniques for audio use-cases
Communicate the experimental results and the recommendations clearly, both within the group as well as to the cross-functional groups
Other
Currently is in the process of obtaining a PhD in the field of AI/ML and Audio/Speech Signal Processing
Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment
Intent to return to degree-program after the completion of the internship
Experience solving complex problems and comparing alternative solutions, trade offs, and diverse points of view to determine a path forward
Experience working and communicating cross functionally in a team environment
