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We are looking for a passionate and talented Applied Scientist who will collaborate with other scientists and engineers to leverage Artificial Intelligence (AI), Machine Learning (ML), and Optimization techniques to solve diverse problems in manufacturing and other industries. As a Gaussian Applied Scientist, you will design and run experiments, develop new algorithms, and find new ways of reducing cost and maximizing performance and reliability of manufacturing systems. Besides theoretical analysis and innovation, you will work closely with seasoned scientists, engineers, and program managers to deliver your algorithms and models into real products. Your work will directly impact our customers in manufacturing lines.

You are the ideal candidate if you are enthusiastic about delivering products and solutions that are robust and dominant in the market. You thrive in ambiguous environments that require finding the best answers to open problems that have not been solved before. You leverage your exceptional technical expertise in fast-paced research and development and apply your fundamental understanding of computer science, mathematics, and statistics to create reliable, scalable high-performance products. Your strong communication skills enable you to work effectively with both business and technical partners. You have hands-on experience making the right decisions about technical methods. You strive for simplicity and elegance, and demonstrate significant creativity and sound judgment backed by real data. Most of all, you are willing to take calculated risks, learn by trying, and grow as a team.


  • Develop cutting-edge, low-level CV algorithms of image enhancement, anomaly detection and pattern recognition for machine vision applications
  • Work with software engineers to develop industrial AI platform and applications
  • Work with PMs to define use cases, collect data, and benchmark the results
  • Contribute to Gauss Labs’s Intellectual Property pools through patents and/or external publications

Key Qualifications

  • BS/MS/PhD degree in Computer Science, Electrical Engineering, Machine Learning, or a related field
  • Track record of publications in CVPR, ECCV, ICCV, TPAMI, etc.
  • Experience applying Machine Learning to solve complex problems and release SW products
  • Expertise of programming in Python, C++, etc. and using the Deep Learning tools such as PyTorch, TensorFlow, etc.