Meta Reality Labs Research is looking to solve important audio-driven problems for AR/VR applications by creating virtual sounds that are perceptually indistinguishable from reality and redefining human hearing.
Requirements
- 3+ years experience with Python, Matlab, or similar
- 3+ years experience with machine learning software platforms such as PyTorch, TensorFlow, etc
- 2+ years experience building novel computational models in audio or audio-visual or speech application domains using machine learning or signal processing
- 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 statistical modeling techniques and / or signal processing
- Proven track record of achieving results as demonstrated in accepted papers at top computer vision and machine learning related conferences such as CVPR, ECCV, NIPS, ICASSP, InterSpeech etc
Responsibilities
- Research, model, design, develop and test novel audio and speech processing algorithms using machine learning, signal processing, and computer vision
- Collaborate with researchers and engineers across diverse disciplines
- Design and implementation of novel algorithms to solve audio research problems
- Experimental design, implementation, and execution to evaluate new audio technologies
- Collaboration with other researchers across audio and acoustic engineering disciplines
- Communication of research agenda, progress, and results
Other
- Currently has, or is in the process of obtaining, a PhD degree in the field of Computer Science, Artificial Intelligence, Signal Processing, Machine learning, Computer vision, Electrical Engineering, Applied Math, Acoustics Engineering or a related STEM field
- 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 a degree-program after the completion of the internship/co-op
- Experience working and communicating cross functionally in a team environment
