Research Scientist: Computer Vision for Audio
Meta/Reality Labs Research brings together a world-class team of researchers, developers, and engineers to create the future of virtual and augmented reality, which will become as universal and essential as smartphones and personal computers are today. And just as personal computers have done over the past 45 years, AR and VR will ultimately change everything about how we work, play, and connect. We are developing all the technologies needed to enable breakthrough AR glasses and VR headsets, including optics and displays, computer vision, audio, graphics, brain-computer interface, haptic interaction, eye/hand/face/body tracking, perception science, and true telepresence. Some of those breakthroughs will advance much faster than others, but they all need to happen to enable AR and VR that are so compelling that they become an integral part of our lives. The audio team at Meta/Reality Labs Research is looking for experts in machine learning and computer vision. This role is focused in design, development and engineering of advanced computer vision systems that drive AV experiences design and synthesis in AR and VR. An ideal candidate will be passionate about the development of advanced proof-of-concept demonstration platforms and about pushing the state-of-the art by conducting fundamental research.
Research Scientist: Computer Vision for Audio Responsibilities:
- Independently implement state-of-the-art models and techniques on PyTorch, TensorFlow or other platforms.
- Independently identify, motivate, and execute on medium to large hypotheses (each with many tasks) for model improvements through data analysis, and domain knowledge, and are able to communicate your learnings effectively.
- Design, perform, and analyze online and offline experiments with specific and well thought-out hypotheses in mind.
- Generate reliable, correct training data with great attention to detail.
- Identify and debug issues in training machine learning models such as overfitting/underfitting, leakage, offline/online inconsistency consistently.
- Understand the model architecture used, and the pros and cons of this for different hypotheses tested. In general, you have a good understanding of computer vision from an applied perspective, even though you may not be up-to-date with the state-of-the-art.
- PhD in the field of Deep learning, Machine Learning, Computer Vision, Computer Science, Computer Engineering or Statistics or a related field.
- Must obtain work authorization in country of employment at the time of hire, and maintain ongoing work authorization during employment.
- 4+ years experience with development and implementation of computer vision or deep learning algorithms.
- 3+ years experience with scientific programming languages such as Python, C++, or similar.
- Demonstrated experience in implementing and evaluating work and end-to-end prototypical learning systems.
- Experience with AV learning or egocentric learning, scene understanding, audio signal processing or similar.
- Experience working with acoustic or speech datasets.
- Proven track record of achieving significant results and innovation as demonstrated by first-authored publications and patents.
- Interpersonal skills: cross-group and cross-culture collaboration.