Sr. R&D Engineer

Vitro Architectural Glass manufactures a broad range of industry-leading, energy-efficient products such as Solarban®, Sungate® and Starphire Ultra-Clear® glasses. Throughout our storied history, collaboration and innovation have been central to our advancements. Today, the key to our success continues to lie in the strength of our partnerships. With a foundation formed on trust, teamwork and shared excitement, the possibilities for impactful innovations in glass are truly endless. With manufacturing facilities throughout the U.S. and Mexico, Vitro Architectural Glass is committed to sustainable manufacturing processes and products. Vitro also operates one of the world’s largest glass research and development facilities in Pittsburgh, PA and has four residential glass fabrication plants in Canada. Website: The Process Engineering and Process Control group within Vitro Architectural Glass R&D is seeking a highly motivated Research Scientist to lead technology development in process modeling and control for next-generation glass manufacturing. The ideal candidate combines a strong foundation in process control with the curiosity, adaptability, and technical breadth to develop innovative solutions and expand into emerging areas such as data science, machine learning, and artificial intelligence. This position is located at our Glass Technology Center in Cheswick, PA, approximately 25 minutes from downtown Pittsburgh. Responsibilities Develop and implement advanced process control solutions using methods such as PID, MPC, feedforward, and inferential control, etc. Develop process models first-principles, system identification, data-driven, and machine learning approaches. Investigate and apply emerging technologies including artificial intelligence and advanced analytics to process monitoring, prediction, control, and optimization. Communicate technical findings through reports, presentations, and research publications to audience from diverse backgrounds. Travel up to 10-15% as required to support project launch and execution. Qualifications Ph.D. in Chemical Engineering, Mechanical Engineering, Applied Mathematics, or a related STEM discipline Strong foundation in process dynamics and control, with demonstrated knowledge of at least one process control methodology such as PID, MPC, feedforward, inferential, or adaptive control Knowledge of optimization methods such as LP, QP, NLP or related numerical techniques Programming experience in Python, MATLAB, C++, or similar computing environments Experience with data analysis, statistical modeling, machine learning, or related analytical methods Strong written and verbal communication skills #J-18808-Ljbffr