About The Position

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.

Requirements

  • Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
  • PhD in the field of machine learning, computer science, robotics, computational neuroscience, signal processing, speech and language technologies, or related fields
  • 2+ years industry experience in deep learning, artificial intelligence, machine learning, computer science, robotics, computer vision, computational neuroscience, signal processing, or related fields
  • Programming experience in Python and hands-on experience with frameworks such as PyTorch
  • Research-oriented software engineering skills, including fluency with libraries for scientific computing (e.g. SciPy ecosystem)
  • Experience with quantitative methods (mathematics, statistics) and experience acquiring new technical knowledge and skills rapidly

Nice To Haves

  • Experience bringing machine learning-based products from research to production
  • Experience in the analysis and modeling of high dimensional time series, such as neural signals, other physiological signals, audio recordings, robotic sensory signals, financial time series, video, or other sensor modalities
  • 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)

Responsibilities

  • Design methods, tools and infrastructure to analyze and leverage rich multimodal data sets
  • Help transition algorithms and metrics from research into production
  • Analyze and develop metrics for deep learning models and experimental datasets
  • Design experiments, involving human participants, to assess model performance
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