Head of Machine Learning & Data Science

We seek an experienced ML/AI manager to lead the Machine Learning and Data Science team. The ideal candidate is strong in both practical and fundamental R&D, having deep and broad expertise in several applied science disciplines. The talent we're looking for should have a good overall understanding of state-of-the-art machine learning algorithms and tools. We want a candidate with a track record of managing applied scientists and AI engineers, demonstrating how to lead and manage a team effectively.

Industrial AI problems require multiple disciplines, great insight to recognize problem structures and technical challenges to overcome, and the capability to devise creative solutions for solving diverse AI problems. Good publication records (e.g., NeurIPS, ICML, ICLR, AAAI, etc.) and good knowledge and experience of computer science and engineering are strong pluses. The candidate should also have extensive experience and skills in collaboration with software engineering teams to keep his/her team from being siloed.

Responsibilities

• 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.

Key Qualifications

• 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.

Preferred Qualifications

• Ph.D. specializing in AI, machine learning, data science, statistics, or related fields.
• Research experience in machine learning and data science handling time-series data, predictive modeling, and anomaly detection.
• Proven achievements in developing and managing a long-term research vision and portfolio of research initiatives, with algorithms and models that have been successfully integrated into production systems.
• Project management experience working with cross-functional teams in multiple geographic locations.
• Ability to translate informal customer requirements into technical problem definitions, dealing with ambiguity and competing objectives.
• Excellent written and verbal communication skills with the ability to present complex technical information clearly and concisely to various audiences.