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Research Scientist
1 month ago
Reality Labs at Meta is seeking Research Scientists with experience in product-focused machine learning and signal processing research to advance our pioneering work in neuromotor interfaces, which has grown out of the acquisition of CTRL-labs. We're building a practical interface drawing on the rich neuromotor signals that can be measured non-invasively via surface electromyography (EMG) with single motor neuron resolution. This technology could become one of the main pillars for interaction with virtual and augmented worlds. We are a multi-disciplinary team of researchers investigating the nature of human neuromotor signals, developing novel signal processing and machine learning methods to infer a user's intent, and creating novel interaction techniques and user experiences. Help us unleash human potential by removing the bottlenecks between user intent and action.
Research Scientist - Reality Labs Responsibilities
- Research and develop Deep Learning or other computational models.
- Design methods, tools and infrastructure to analyze and leverage rich multimodal data sets.
- Set technical direction for a project of 2-3 researchers and engineers.
- Help transition and deliver our work from research into product.
- Adapt standard machine learning methods to best leverage modern parallel environments (e.g. distributed clusters, multicore SMP, and GPU)
- Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.
- Ph.D. degree in Computer Science and Engineering, Electrical Engineering, Statistics/Mathematics.
- Experience with developing machine learning models at scale from inception to business impact.
- Programming experience in Python and hands-on experience with frameworks such as PyTorch.
- Exposure to architectural patterns of large scale software applications.
- Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment.
- First-author publications at peer-reviewed AI conferences (e.g. NeurIPS, CVPR, ICML, ICLR, ICCV, ACL, and ICASSP).
- Experience in software engineering in industry.
- Experience bringing machine learning-based products from research to production.
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