Sr. Engineer, Advanced Process Controls

Corning•Town of Erwin, NY

8d•$88,834 - $122,148•Onsite

About The Position

MT&E is seeking an Advanced Process Controls Engineer who believes cutting-edge controls, optimization, and machine learning (ML) can transform manufacturing and deliver competitive advantage. This is one of the most versatile technical roles at Corning, with broad scope across our businesses. The field is evolving from traditional single-input/single-output control toward complex multi-input/multi-output problems that call for model-based strategies, most notably model predictive control (MPC), and large-scale numerical optimization for production planning, scheduling, and ware flow. Corning is also investing in machine learning for process monitoring, fault detection, defect classification, and predictive maintenance.

Requirements

M.S. or PhD in Electrical, Mechanical, or Chemical Engineering (or a related field) with coursework in Advanced Controls, Optimization, or Data Analytics. PhD highly preferred.
1–5 years of industry experience on manufacturing processes. New graduates with related internship experience will be considered.
Working knowledge of process control technologies, including MPC and PID; practical PID loop tuning experience.
Controls-oriented modeling and system identification.
Grounds control design in process first principles (heat/mass transfer, fluid dynamics, kinetics).
Foundation in numerical optimization (LP, NLP, MILP, convex optimization) and ability to formulate problems from business and process logic.
Programming experience in MATLAB/Simulink and Python.
Familiarity with ML classification and regression techniques.
Strong problem-solving skills; clear written and verbal communication for technical and non-technical audiences.
Comfortable working in a manufacturing environment.
Self-directed and collaborative; delivers on commitments

Nice To Haves

Hands-on experience implementing, tuning, and maintaining MPC.
Experience with large-scale optimization solvers (e.g., Gurobi) and modeling languages (Pyomo, AMPL, PuLP).
Multivariate statistical process control methods such as PCA and PLS regression.
Experience operationalizing ML-driven models in manufacturing.
Git and version control.
Experience in or leading cross-functional and global teams.
Strong technical curiosity and appetite for hard technical problems.

Responsibilities

Design, develop, and implement controls solutions for manufacturing processes within multi-disciplinary teams.
Evaluate existing control strategies and propose enhancements, from PID improvements (cascade, feedforward, gain-scheduling, loop pairing) to model-based algorithms such as MPC and internal model control (IMC).
Develop and maintain MPC-based solutions across the organization.
Build and improve large-scale optimization models (LP, NLP, MILP) for production planning and scheduling, translating business and process logic into objectives and constraints.
Partner with manufacturing to define appropriate hardware and software platforms and implement solutions in existing PLC/DCS environments.
Work with subject matter experts and apply data analytics and ML to deepen process understanding and surface control or optimization opportunities.
Apply multivariate statistics and ML to fault diagnosis and isolation, defect classification, and predictive maintenance.
Lead projects in a research, development, and engineering environment; write proposals to initiate new work.
Facilitate transfer of new technologies into manufacturing and train manufacturing and engineering personnel.
Generate intellectual property through technical reports, invention disclosures, and patents.