About Us: Avitas Systems is a wholly owned subsidiary of GE, the world’s Digital Industrial Company. At GE and Avitas we are transforming industry with software-defined machines and solutions that are connected, responsive and predictive. Through our people, leadership development, services, technology and scale, Avitas delivers better outcomes for global customers by speaking the language of industrial inspection.
Avitas offers a great work environment, professional development, challenging careers, and competitive compensation. Avitas is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other characteristics protected by law.
GE offers a great work environment, professional development, challenging careers, and competitive compensation. GE is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other characteristics protected by law.
Role Summary: The Staff Computer Vision Scientist would be a key member of the Advanced Analytics and Machine Learning team that will be responsible for curating and analyzing large sets of business and operations data of Avitas' customers across several industry verticals. This specific role would be to apply advanced analytics and machine learning techniques for tagging, classification, and automating feature and object recognition in images and video streams.
Essential Responsibilities: The Staff Computer Vision Scientist will also very closely work with Subject Matter Experts and Business Analysts to rapidly understand a specific business domain and iteratively refine the analyses and the learning models to create high-fidelity automated analytics solutions.
Responsibilities include but are not limited to:
Work closely with Subject Matter Experts to collect requirements for various Computer Vision based applications
Conduct Computer Vision research, including collaborating with GE Global Research Team, and transition cutting edge computer vision out of the labs into the field
Investigate and apply image analytics and machine learning approaches and tools for detecting content of outdoor industrial asset images
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