AI Research Scientist, Neuromotor Interfaces, ML & Signal Proc
Burlingame, CA | New York, NY
Meta
Giving people the power to build community and bring the world closer togetherWe are a multi-disciplinary team of researchers building text input methods using human neuromotor signals (i.e., electromyography or EMG). EMG signals are similar in many ways to other neural signals and audio signals and can be analyzed using many of the same approaches. For example, the task of transcribing characters typed on a keyboard from wrist-based EMG is closely analogous to that of automatic speech recognition. We’re looking for people who want to shape the future of this technology and explore this exciting new territory with us.AI Research Scientist, Neuromotor Interfaces, ML & Signal Proc Responsibilities
- Build cutting-edge machine learning and signal processing models (event detection, sequence-to-sequence, signal separation, time series regression, etc.) to advance neuromotor interface capabilities.
- Collaborate with engineering and Human-Computer Interactions (HCI) teams to deploy models that leverage fundamental scientific knowledge into new technology and user experiences.
- Use quantitative research methods to define, iterate upon and advance key areas of our research agenda.
- Develop research-grade code for deployment in research prototypes.
- Set technical direction for a project of 2-3 researchers and engineers.
- PhD in one of the following fields: deep learning, artificial intelligence, machine learning, computer science, robotics, computer vision, computational neuroscience, signal processing, speech and language technologies, or related fields.
- Research-oriented software engineering skills, including fluency with libraries for scientific computing (e.g. SciPy ecosystem) and machine learning (e.g., PyTorch, TensorFlow, Scikit-learn, Pandas).
- Proficiency with quantitative methods (mathematics, statistics) and experience learning new technical knowledge and skills rapidly.
- Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.
- 5+ years of experience working autonomously to design, execute, interpret, and present research studies.
- 2+ years of experience as technical lead for a project of 2-3 individuals.
- Experience bringing machine learning-based products from research to production.
- Experience with interdisciplinary and/or cross-cultural collaboration.
- Experience in the analysis and modeling of high dimensional time series, such as neural signals, multi-channel audio recordings, multi-modal/multi-sensor signals, robotic sensory signals, financial time series, video, or other sensor modalities.
- Experience with speech enhancement, speech recognition, speech synthesis, source separation, audio event detection and classification, audio scene recognition, microphone arrays, beamforming, or related topics.
- Experience with real-time signal processing and/or human-computer interaction.
- Experience with large scale cluster computing for machine learning modeling.
- Experience developing end-to-end ML pipelines, including: dataset preprocessing, model development and evaluation, and software integration.
- Experience in software engineering in industry.
- Experience with scientific communication tools (Jupyter, Matplotlib).
Individual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base compensation, Meta offers benefits. Learn more about benefits at Meta.
Tags: ASR Classification Computer Science Computer Vision Deep Learning Engineering Jupyter Machine Learning Mathematics Matplotlib ML models NLP Pandas PhD Physics Pipelines PyTorch Research Robotics Scikit-learn SciPy Speech synthesis Statistics TensorFlow VR
Perks/benefits: Career development Equity / stock options Health care Salary bonus
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