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Model Predictive Control Jobs in Texas (NOW HIRING)

Avride

Lead Software Engineer - Control

Austin, TX

This role is roughly 80% hands-on engineering and 20% technical leadership - you'll spend most of your time architecting and shipping Model Predictive Control (MPC) systems and vehicle dynamics ...

Avride

Lead Software Engineer - Control

Austin, TX · On-site

This role is roughly 80% hands-on engineering and 20% technical leadership - you'll spend most of your time architecting and shipping Model Predictive Control (MPC) systems and vehicle dynamics ...

Delek US

Staff Process Controls Engineer

Tyler, TX

$78K - $101K/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 ...

Base Power Company

Algorithms Engineer

Austin, TX · On-site

Deep understanding of any number of control or control-adjacent disciplines: e.g. model predictive control, reinforcement learning, Markov decision processes, signal processing. * A data-driven ...

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Model Predictive Control information

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 are the typical challenges faced by engineers working with model predictive control 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 are the key skills and qualifications needed to thrive as a model predictive control 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 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 does a model predictive control do?

A Model Predictive Control (MPC) engineer designs control systems that use a mathematical model to predict future system behavior and optimize control actions accordingly. MPC is commonly used in industries like process control and robotics, requiring skills in control theory, programming, and system modeling. The role involves developing algorithms, tuning controllers, and ensuring system stability and efficiency.

What are popular job titles related to Model Predictive Control jobs in Texas?

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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
Infographic showing various Model Predictive Control job openings in Texas as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 19% Part Time, 4% Contract, and 2% Nights. Highlights an 95% Physical, 1% Hybrid, and 4% Remote job distribution.

Lead Control Systems Engineer

The Woodlands, TX

Linde
See more jobs at Lindeexternal

Full-time

Re-posted 13 days ago

Linde rating

8.1

Company rating: 8.1 out of 10

Based on 82 frontline employees who took The Breakroom Quiz

Job description

  • You will beresponsible for the design, development, and execution of control systems forlarge industrial facilities
  • Further, you willdevelop control narratives, IO Index, cause and effects, control logic, andoperator graphics for DCS, PLC, BMS systems
  • Additionally, youhave thorough knowledge of Process Automation includingdesign/implementation of complex control strategies, turbomachinery controls,and model predictive control (MPC) 
  • You will also berequired to attend and conduct Factory Acceptance Tests, Site Acceptance Tests,and participate in commissioning and startup activities
  • You will configurethe 3rd party device endpoints using serial, Modbus TCP, Ethernet/IP orProfibus communication protocols
  • You will participatein HAZOP, LOPA, and other Safety Lifecycle work processes as outlined in IEC61511, CFSE Certification is a plus
  • Also, you will managethe interface between vendors and engineering contractors when the work isoutsourced to third party integrators and contractors 
  • You will managetechnical project deliverables using internal and external resources whileencouraging Linde's global workshare partnerships and philosophies
  • You will assist inpreparation of key quantities and estimates of control systems for capitalproject proposals

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