Research Engineer, Neuromotor Interfaces

2 weeks ago

Burlingame, United States META Full time

Meta Reality Labs is looking for a Research Engineer to help us unleash human potential by eliminating the bottlenecks between intent and action. To achieve this, we're building a practical neural interface drawing on the rich neuromotor signals that can be measured non-invasively using electromyography (EMG). Our research lies at the intersection of computational neuroscience, machine learning, signal processing, statistics, biophysics, motor learning, AR/VR and human-computer interaction.

Research Engineer, Neuromotor Interfaces Responsibilities

  • Plan and execute cutting-edge applied research to advance neuromotor interface capabilities.
  • Design experiments to collect neuromotor and interaction data and evaluate human and model performance.
  • Design methods, tools and infrastructure to analyze and leverage rich multimodal data sets.
  • Define short-term research goals, informed by practical engineering concerns.
  • Collaborate with research scientists and research engineers to deploy models that leverage fundamental scientific knowledge into new technology and user experiences.
  • Help transition and deliver our work from research into product.
Minimum Qualifications
  • Currently has, or is in the process of obtaining a Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience. Degree must be completed prior to joining Meta.
  • Research-oriented software engineering skills, including fluency in python and in libraries for scientific computing (e.g. SciPy ecosystem, Pandas)
  • Masters degree in Computer Science, Computer Engineering, or relevant technical field.
  • Proficiency with quantitative methods (mathematics, statistics) and experience learning new technical knowledge and skills rapidly.
  • Must obtain work authorization in country of employment at the time of hire and maintain ongoing work authorization during employment.
  • Exposure to architectural patterns of large scale software applications.
  • Experience with interdisciplinary and/or cross-cultural collaboration.
Preferred Qualifications
  • PhD in one of the following fields: deep learning, artificial intelligence, machine learning, computer science, robotics, computer vision, computational neuroscience, signal processing, or related fields.
  • Autonomously set technical and research direction.
  • Comfort with rapid prototyping and disciplined software development processes.
  • Experience developing end-to-end ML pipelines, including: dataset preprocessing, model development and evaluation, and software integration.
  • Experience in software engineering in industry.
  • Experience bringing machine learning-based products from research to production.
  • Experience with scientific communication tools (Jupyter, Matplotlib).
  • Research and software engineer experience demonstrated via an internship, contributions to open source, work experience, or coding competition


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