Key skills
PythonAIMachine LearningDeep LearningPyTorchGitHub
About this role
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.
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)
Qualifications
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 Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as first-authored publications at peer-reviewed AI conferences (e.g. NeurIPS, CVPR, ICML, ICLR, ICCV, ACL, and ICASSP)
* Demonstrated software engineer experience via an internship, work experience, coding competitions, or widely used contributions in open source repositories (e.g. GitHub)
* Experience bringing machine learning-based products from research to production
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.
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)
Qualifications
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 Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as first-authored publications at peer-reviewed AI conferences (e.g. NeurIPS, CVPR, ICML, ICLR, ICCV, ACL, and ICASSP)
* Demonstrated software engineer experience via an internship, work experience, coding competitions, or widely used contributions in open source repositories (e.g. GitHub)
* Experience bringing machine learning-based products from research to production