Head of Machine Learning & Data Science

April 11

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Gauss Labs

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We normalize AI. We revolutionize manufacturing.

Industrial AI • Machine Learning • Data Science • Virtual Metrology • Manufacturing AI

11 - 50

Description

• Conduct and coordinate research leading to large-scale ML projects for industrial AI. • Lead applied scientists to develop experiments, algorithms, and prototypes that advance the state-of-the-art in industrial AI. • Provide technical and scientific guidance to the team members and support their career development. • Develop cutting-edge ML algorithms such as online regression, classification, supervised/unsupervised learning, anomaly detection, and hybrid ML algorithms. • Lead projects with complete independence and help from PMs even when business, product, and technical strategies are not defined and the problems to be solved are not known. • Work with PMs to define use cases, collect data, and benchmark the results. • Work with software engineering teams to develop industrial AI platforms and applications. • Contribute to Gauss Labs's intellectual property pools by publishing patents and technical papers. • Communicate effectively with senior management as well as with colleagues from science, engineering, and business backgrounds.

Requirements

• Master's degree in applied research for machine learning and data science, or a highly relevant field. • Deep and broad expertise across several applied science disciplines, being scientifically versatile and demonstrating scientific and industrial maturity. • 10+ years of experience in applying AI/ML to solve complex business problems for large-scale applications. • 5+ years of experience managing machine learning and data scientists and engineers. • Hands-on experience programming in Python, Matlab, R, Java, C++, or other programming languages.

Benefits

• Good publication records (e.g., NeurIPS, ICML, ICLR, AAAI, etc.) and good knowledge and experience of computer science and engineering are strong pluses. • Extensive experience and skills in collaboration with software engineering teams • 11 paid holidays • Generous Accru watched Time Off increasing with years of service