Rendered.ai
Sean Owens has a strong background in software engineering and development. Sean started their career as a Teaching Assistant and Research Assistant at Mississippi State University, where they worked on various projects related to interactive visualization techniques and the feasibility of applying FPGA partial reconfiguration techniques for space programs. During this time, they also participated in the NSF GK12 Outreach program, where they taught high school geometry and created hands-on exercises to stimulate interest in STEM subjects.
After their time at the university, Sean worked as a Technician at Professional Computers of Louisiana, providing on-site technology support for a large office. Sean was responsible for maintaining workstations, resolving client issues, and performing software updates. Following this, they joined Allscripts as a Software Engineer, where they designed and developed front-end web applications for the FollowMyHealth healthcare patient portal. Sean also worked on upgrading the existing Dashboard application to the AngularJS platform.
Most recently, Sean has held roles at Doma and Rendered.ai as a Senior Frontend Developer and Senior Frontend Engineer, respectively. These roles showcase their expertise in frontend development and their ability to contribute to the success of web applications.
Overall, Sean Owens has a diverse range of experience in software engineering and development, with a focus on frontend technologies and application design.
Sean Owens earned a Bachelor of Science degree in Computer Engineering from Mississippi State University in the years 2007 to 2011. Following this, they pursued a Master's degree in Computer Engineering from the same university, completing it in the years 2011 to 2013.
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Rendered.ai
Rendered.ai is a platform-as-a-service for data scientists, data engineers, and developers who need to create and deploy unlimited, customized synthetic data generation for machine learning and artificial intelligence workflows, reducing expense, closing gaps, and overcoming bias, security, and privacy issues when compared with the use or acquisition of real-world data.