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Research Scientist
2 months ago
Research Scientist - Wearables, Input & Interaction (Technical Leadership) 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.
- Work across organizational boundaries to solve our biggest problems.
Minimum Qualifications:
- 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.
- Must obtain work authorization in country of employment at the time of hire and maintain ongoing work authorization during employment.
- Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.
Preferred Qualifications:
- 8+ years of experience working autonomously to design, execute, interpret, and present research studies.
- 4+ years of experience as technical lead for a project of 4 or more 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).
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