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
Minimum Qualifications
- 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
Preferred Qualifications
- 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)
$154,000/year to $217,000/year + bonus + equity + benefits
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