Responsibilities

• 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.
• Collaborate with other applied scientists to experiment, and develop algorithms/prototypes that advance the state-of-the-art in industrial AI.
• Work with software engineers to provide support for scaling and productization of algorithms.
• Work with PMs to define use cases, collect data, and benchmark the results.
• Lead projects independently and help PMs in a dynamic environment where business, product, and technical strategies are evolving even when problems are not well understood yet.
• Contribute to Gauss Labs’s intellectual property pools through patents and technical publications.
• Contribute to Gauss Labs’s research advancement by publishing technical papers at external conferences and journals.

Key Qualifications

• Ph.D. in Artificial Intelligence, Machine Learning, Computer Science, Electrical Engineering, Computer Vision, Statistics, or related fields.
• 3+ years of experience doing exceptional Machine Learning research as demonstrated by both scientific publications in top venues and solutions to resolve complex business problems for potential industrial impact
• Hands-on experience programming in Python, R, C++, Java, or other modern programming languages.
• Experience in large-scale ML systems and related technologies, including commercial cloud stacks, resource provisioning/orchestration, and scaling methodologies (e.g., distributed optimization).