Developing the next generation of speech and audio enhancement algorithms for wearables in various acoustic environments to transform entertainment and social experiences at Meta
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
- 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
- Deep subject matter expertise in one or more areas in speech/audio signal processing such as: 1) Speech Synthesis and/or Audio playback signal processing algorithms (compressors, limiters, EQs, and Automatic Gain Control (AGCs)), 2) Adaptive system identification, noise reduction, sound source localization, beamforming, adaptive filters (echo/feedback cancellation), 3) Spatial audio and room acoustics
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
- Demonstrated software engineer experience via an internship, work experience, coding competitions, or widely used contributions in open source repositories (e.g. Github)
- Experience working and communicating cross functionally in a team environment
