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Applied Scientist - Machine Learning (US / KR)
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- You are supposed to be strong in both practical R&D and fundamentals with deep and broad expertise in several or at least a few applied science disciplines.
- Develop cutting-edge Machine Learning algorithms in time-series or computer vision domain and technical areas such as online classification, regression, supervised/unsupervised learning, reinforcement learning, anomaly detection, pattern recognition, image restoration/denoising, object detection/segmentation, or hybrid ML algorithms.
- Work with PMs to define use cases, collect data, and benchmark the results.
- Contribute to Gauss Labs's intellectual property pools through patents and technical publications.
- Ph. D. in Artificial Intelligence, Machine Learning, Computer Science, Electrical Engineering, Computer Vision, Statistics, or related fields.
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