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Model Predictive Control Jobs in Texas (NOW HIRING)

Covestro

Senior APC Engineer

Baytown, TX

$95.10K - $130.70K/yr

Identifyand initiate projects in the fields ofexpertise(Dynamic Modeling, Operator Training Simulators, Advanced Control and Model Predictive Control as well as multivariate data analysis)

Covestro AG

Principal APC Engineer

Baytown, TX · On-site

Identify and initiate projects in the fields of expertise (Dynamic Modeling, Operator Training Simulators, Advanced Control and Model Predictive Control as well as multivariate data analysis)

Covestro

Principal APC Engineer

Baytown, TX

Identifyand initiate projects in the fields ofexpertise(Dynamic Modeling, Operator Training Simulators, Advanced Control and Model Predictive Control as well as multivariate data analysis)

Covestro AG

Senior APC Engineer

Baytown, TX · On-site

$95.10K - $130.70K/yr

Identify and initiate projects in the fields of expertise (Dynamic Modeling, Operator Training Simulators, Advanced Control and Model Predictive Control as well as multivariate data analysis)

Avride

C++ Software Engineer - Control

Austin, TX

In this role, you will architect sophisticated control systems using Model Predictive Control (MPC) and identify the dynamic parameters of our vehicles. What You'll Do * Design, implement, and ...

Avride

C++ Software Engineer - Control

Austin, TX · On-site

In this role, you will architect sophisticated control systems using Model Predictive Control (MPC) and identify the dynamic parameters of our vehicles. What You'll Do * Design, implement, and ...

Delek US

Staff Process Controls Engineer

Tyler, TX

$78.70K - $101.80K/yr

Development, design, and commissioning of MPC (Model Predictive Control) applications and provide support for existing APC and/or Real-Time Optimizer applications * Act as technical lead for all unit ...

Delek US

Staff Process Controls Engineer

Tyler, TX · On-site

Development, design, and commissioning of MPC (Model Predictive Control) applications and provide support for existing APC and/or Real-Time Optimizer applications * Act as technical lead for all unit ...

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Model Predictive Control information

What are the key skills and qualifications needed to thrive as a Model Predictive Control (MPC) Engineer, and why are they important?

To thrive as a Model Predictive Control Engineer, you need strong foundations in control theory, applied mathematics, and process engineering, usually supported by a degree in engineering or a related field. Proficiency with simulation tools such as MATLAB/Simulink, programming languages like Python or C++, and familiarity with industrial automation systems are typically required. Analytical thinking, problem-solving abilities, and effective communication skills help distinguish top performers in this role. These skills are essential for designing, implementing, and optimizing advanced control algorithms that improve system performance and reliability in complex industrial environments.

What are the typical challenges faced by engineers working with Model Predictive Control (MPC) systems in an industrial setting?

Engineers working with Model Predictive Control systems often encounter challenges related to model accuracy, computational demands, and real-time implementation. Ensuring the process model accurately represents the plant dynamics is critical, as discrepancies can lead to suboptimal control performance. Additionally, MPC algorithms can be computationally intensive, particularly for large-scale or fast processes, requiring careful tuning and optimization to maintain real-time operation. Collaboration with process engineers and IT specialists is common, as integrating MPC with existing control systems and plant infrastructure is a key part of the role.

What is Model Predictive Control?

Model Predictive Control (MPC) is an advanced method of process control that uses a mathematical model to predict and optimize the future behavior of a system. It works by solving an optimization problem at each control step to determine the best sequence of control actions, taking into account system constraints and objectives. MPC is widely used in industries such as chemical processing, energy, and automotive because it can handle multivariable control problems and anticipate future events. Its predictive nature allows for improved performance, stability, and efficiency compared to traditional control methods.

What is the difference between Model Predictive Control vs Control Systems Engineer?

AspectModel Predictive ControlControl Systems Engineer
CredentialsEngineering degree, control theory, process modelingEngineering degree, control systems, automation
Work EnvironmentIndustrial automation, process control, manufacturingDesign, develop, and maintain control systems across industries
Industry UsageProcess industries, chemical, oil & gas, manufacturingAutomation, robotics, embedded systems, industrial sectors

Model Predictive Control (MPC) focuses on advanced control algorithms for optimizing processes, while Control Systems Engineers design and implement various control systems. MPC is a specialized skill within control engineering, often requiring knowledge of process modeling and optimization, whereas Control Systems Engineers have broader responsibilities across multiple control technologies. Both roles are essential in industrial automation but differ in scope and application.

What are popular job titles related to Model Predictive Control jobs in Texas? For Model Predictive Control jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Model Predictive Control jobs in Texas look for? The top searched job categories for Model Predictive Control jobs in Texas are:
What cities in Texas are hiring for Model Predictive Control jobs? Cities in Texas with the most Model Predictive Control job openings:
Model Predictive Control jobs near you
Advanced Process Control Engineer - Irving TX

Advanced Process Control Engineer - Irving TX

Matheson Tri-Gas, Inc.

Irving, TX • On-site

Other

Posted 21 days ago

Matheson rating

8.0

Company rating: 8.0 out of 10

Based on 47 frontline employees who took The Breakroom Quiz

23rd of 74 rated oil and gas companies

Job description

JOB SUMMARY

The Advanced Process Control (APC) Engineer role is based out of the Irving, Texas office. Their primary responsibility is for the design, implementation, and maintenance of advanced process control strategies (MPC) and AI-driven models to optimize manufacturing performance, yield, and energy efficiency for a fleet of Air Separation Units (ASU). Additionally, this role maintains responsibility for PLC programming, HMI development, and troubleshooting to ensure reliable, high-level automation functionality.

 

Essential Functions

Essential Function

         Lead the design, develop, implement, and maintain Model Predictive Control (MPC) and AI-based empirical models to optimize process variables and reduce variability.

         Apply AI and machine learning techniques (e.g., reinforcement learning, neural networks) to process data for predictive analytics, digital twins, and autonomous control adjustments.

         Lead commissioning work with operations and instrumentation engineers to commission and tune AI/APC applications on-site, ensuring seamless integration with the existing DCS.

         Continuously analyze system data to identify bottlenecks, meet production targets, reduce energy consumption, and increase throughput, yield, and profitability.

         PLC Coding: Develop and troubleshoot PLC programs (Ladder Logic, Structured Text) on ControlLogix or Siemens platforms to support new or existing machinery.

         HMI/SCADA: Configure and maintain HMI screens (FactoryTalk View, Wonderware) to ensure effective operator interfaces.

         System Integration: Integrate APC/AI software layers with underlying PLCs to ensure seamless communication (Ethernet/IP, OPC UA).

         Maintenance & Troubleshooting: Perform on-site troubleshooting of PLC faults, field instruments, and motor drives.

         Data: Global Historian, standardize trending, KPI development & data visualization with Power BI

         Documentation: Maintain up-to-date control narratives, P&IDs, electrical schematics, and functional specifications.

         Provide technical training and documentation to ensure high APC uptime and proper response to system constraints.

         Utilize process simulation tools (e.g., Aspen HYSYS) to validate control models against actual plant data

         Identify opportunities to modernize legacy control systems and integrate "smart" automation features into our standard operating procedures.

         Follow all aspects of change management (P&IDs, EMOC, etc.)

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Performs other duties as assigned

Complies with all policies and standards

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