We are looking for experienced and accomplished AI Scientists for Computer Vision R&D. 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 AI disciplines. You should have a good understanding of the state-of-the-art ML and CV algorithms and methods, exceptional publication records (e.g., NeurIPS, ICML, ICLR, KDD, CVPR, ICCV, etc.), and good knowledge and experience in computer science and engineering (e.g., how to use CPUs/GPUs for efficient training and inference for diverse use cases). You should also have experience and skills in collaboration with software engineering teams to enable the scaling and productization of ML algorithms.
Responsibilities
Develop cutting-edge Machine Learning and Computer Vision algorithms in multi-dimensional data domain and technical areas such as classification, regression, segmentation, anomaly detection, pattern recognition, supervised/unsupervised/self-supervised/multimodal/transfer learning, and effective model architecture such as graph neural network.
Collaborate with other AI scientists to experiment and develop algorithms/prototypes that advance state-of-the-art industrial AI.
Work with software engineers to provide support for scaling and productization of algorithms.
Work with project managers and product managers to define use cases, collect data, and benchmark the results.
Lead projects independently and help project managers 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. or MS in Machine Learning, Computer Vision, Computer Science, Electrical Engineering, or related fields.
5+ years of experience doing exceptional Machine Learning and Computer Vision 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 or other modern programming languages.
Preferred Qualifications
Experience in large-scale ML systems and related technologies, including commercial cloud stacks, resource provisioning/orchestration, and scaling methodologies (e.g., distributed optimization).
