META
Research Scientist, Neural Interfaces - Machine Learning (Inertial Measurement U
META, New York, New York, us, 10261
Research Scientist, Neural Interfaces - Machine Learning (Inertial Measurement Unit)
Join to apply for the
Research Scientist, Neural Interfaces - Machine Learning (Inertial Measurement Unit)
role at
Meta . This range is provided by Meta. Your actual pay will be based on your skills and experience talk with your recruiter to learn more. Base pay range
$147,000.00/yr - $208,000.00/yr Job Description
Meta is seeking a Research Scientist to help us unleash human potential by eliminating the bottlenecks between intent and action. Were building a practical neural interface that leverages motor neuron signals measured non-invasively with neuron-level resolution. Our research spans computational neuroscience, machine learning, signal processing, statistics, biophysics, motor learning, perceptual psychophysics, and human-computer interaction. We want individuals eager to shape the future of this technology and join our collaborative research team. Responsibilities
Research and develop machine learning models utilizing Inertial Measurement Unit sensors. Build advanced machine learning and signal processing models (e.g., event detection, sequence-to-sequence, signal separation, time series regression). Apply quantitative research methods to define, iterate upon, and advance key research areas. Minimum Qualifications
Bachelor's degree in Computer Science, Engineering, or related field, or equivalent practical experience. PhD in machine learning, AI, computer science, electrical engineering, robotics, signal processing, or related fields. At least 1 year of industry experience in AI, machine learning, robotics, or related areas. Experience with hardware sensors such as Inertial Measurement Units. Proficiency with scientific computing and machine learning libraries (e.g., Scikit-learn, PyTorch, TensorFlow). Strong quantitative skills (mathematics, statistics) and ability to learn technical skills rapidly. Preferred Qualifications
Experience analyzing high-dimensional time series (neural signals, audio, robotic sensors, etc.). Developing end-to-end ML pipelines including data preprocessing, modeling, and software integration. Knowledge of signal processing and control theory. First-authored publications in peer-reviewed venues. Experience with large-scale cluster computing for ML. About Meta
Meta builds technologies that connect people, foster communities, and enable businesses. From Facebook to immersive AR/VR, we aim to push beyond current digital limits. We are committed to diversity, equity, and inclusion, providing accommodations for candidates with disabilities. Compensation
Base salary ranges from $147,000 to $208,000 annually, plus bonus, equity, and benefits. Actual compensation depends on skills, experience, and location. Additional Details
This is a full-time position based in New York, NY, or other locations as applicable. #J-18808-Ljbffr
Join to apply for the
Research Scientist, Neural Interfaces - Machine Learning (Inertial Measurement Unit)
role at
Meta . This range is provided by Meta. Your actual pay will be based on your skills and experience talk with your recruiter to learn more. Base pay range
$147,000.00/yr - $208,000.00/yr Job Description
Meta is seeking a Research Scientist to help us unleash human potential by eliminating the bottlenecks between intent and action. Were building a practical neural interface that leverages motor neuron signals measured non-invasively with neuron-level resolution. Our research spans computational neuroscience, machine learning, signal processing, statistics, biophysics, motor learning, perceptual psychophysics, and human-computer interaction. We want individuals eager to shape the future of this technology and join our collaborative research team. Responsibilities
Research and develop machine learning models utilizing Inertial Measurement Unit sensors. Build advanced machine learning and signal processing models (e.g., event detection, sequence-to-sequence, signal separation, time series regression). Apply quantitative research methods to define, iterate upon, and advance key research areas. Minimum Qualifications
Bachelor's degree in Computer Science, Engineering, or related field, or equivalent practical experience. PhD in machine learning, AI, computer science, electrical engineering, robotics, signal processing, or related fields. At least 1 year of industry experience in AI, machine learning, robotics, or related areas. Experience with hardware sensors such as Inertial Measurement Units. Proficiency with scientific computing and machine learning libraries (e.g., Scikit-learn, PyTorch, TensorFlow). Strong quantitative skills (mathematics, statistics) and ability to learn technical skills rapidly. Preferred Qualifications
Experience analyzing high-dimensional time series (neural signals, audio, robotic sensors, etc.). Developing end-to-end ML pipelines including data preprocessing, modeling, and software integration. Knowledge of signal processing and control theory. First-authored publications in peer-reviewed venues. Experience with large-scale cluster computing for ML. About Meta
Meta builds technologies that connect people, foster communities, and enable businesses. From Facebook to immersive AR/VR, we aim to push beyond current digital limits. We are committed to diversity, equity, and inclusion, providing accommodations for candidates with disabilities. Compensation
Base salary ranges from $147,000 to $208,000 annually, plus bonus, equity, and benefits. Actual compensation depends on skills, experience, and location. Additional Details
This is a full-time position based in New York, NY, or other locations as applicable. #J-18808-Ljbffr