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Model Predictive Control Jobs in Colorado (NOW HIRING)

RMH SYSTEMS

Controls Engineer II

Loveland, CO · On-site

$81K - $105K/yr

Experience with advanced control strategies such as PID tuning, model predictive control, or robotics integration. * Familiarity with safety instrumented systems (SIS) and relevant safety standards ...

RMH Systems

Controls Engineer II

Loveland, CO · On-site

$81K - $104K/yr

Experience with advanced control strategies such as PID tuning, model predictive control, or robotics integration. * Familiarity with safety instrumented systems (SIS) and relevant safety standards ...

RMH SYSTEMS

Controls Engineer II

Loveland, CO · On-site

$81K - $105K/yr

Experience with advanced control strategies such as PID tuning, model predictive control, or robotics integration. * Familiarity with safety instrumented systems (SIS) and relevant safety standards ...

EchoStar

Automation Control Engineer II

Denver, CO

$85K - $103K/yr

Practical AI Application skills to enhance data analysis, reporting, predictive maintenance modeling, and control sequence optimization Minimum Requirements: * Minimum Education: Bachelor's degree (B.

EchoStar

Automation Control Engineer II

Denver, CO · On-site

$85K - $103K/yr

Practical AI Application skills to enhance data analysis, reporting, predictive maintenance modeling, and control sequence optimization Minimum Requirements: * Minimum Education: Bachelor's degree (B.

EchoStar

Automation Control Engineer II

Denver, CO · On-site

$85K - $103K/yr

Practical AI Application skills to enhance data analysis, reporting, predictive maintenance modeling, and control sequence optimization Minimum Requirements: * Minimum Education: Bachelor's degree (B.

EchoStar

Automation Control Engineer II

Denver, CO

$85K - $103K/yr

Practical AI Application skills to enhance data analysis, reporting, predictive maintenance modeling, and control sequence optimization Minimum Requirements: * Minimum Education: Bachelor's degree (B.

Engg

Software Engineer I, Data Science (New Grad)

Denver, CO · On-site

$117K - $141K/yr

You'll write SQL queries, build predictive models in Python, create operational dashboards, and see your analysis drive decisions on the manufacturing floor and in mission control. This is a 3 month ...

New

Vizient

AVP, Machine Learning & Modeling

Englewood, CO · On-site

$156K - $290K/yr

... predictive analytics, and optimization. Model Development and Deployment Oversee the design ... control, validation, and ongoing performance monitoring. Partner with risk management and ...

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All JobsModel Predictive Control JobsModel Predictive Control Jobs in Colorado

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 Colorado?

For Model Predictive Control jobs in Colorado, the most frequently searched job titles are:

What job categories do people searching Model Predictive Control jobs in Colorado look for?

The top searched job categories for Model Predictive Control jobs in Colorado are:

What cities in Colorado are hiring for Model Predictive Control jobs?

Cities in Colorado with the most Model Predictive Control job openings:

Model Predictive Control jobs near you
Infographic showing various Model Predictive Control job openings in Colorado as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 19% Part Time, 4% Contract, and 1% Nights. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution.

Controls Engineer II

Loveland, CO • On-site

RMH SYSTEMS
Industrial Automation Equipment Manufacturing • 51 - 200 employees
Learn more about RMH SYSTEMSexternal

$81K - $105K/yr

Full-time

Posted 15 days ago

Job description

About the Role:

The Controls Engineer II plays a critical role in designing, developing, and optimizing control systems that enhance the efficiency and reliability of industrial processes. This position involves collaborating with cross-functional teams to implement automation solutions that meet operational requirements and safety standards. The engineer will be responsible for troubleshooting and resolving complex control system issues to minimize downtime and improve system performance. Additionally, the role requires continuous evaluation and integration of new technologies to advance control strategies and maintain competitive advantage. Ultimately, the Controls Engineer II ensures that control systems operate seamlessly to support the organization's production goals and quality standards.

Minimum Qualifications:

  • Bachelor’s degree in Electrical Engineering, Control Engineering, or a related technical field.
  • 3+ years of experience in control system design, programming, and troubleshooting.
  • Proficiency with PLC programming languages such as Ladder Logic, Structured Text, or Function Block Diagram.
  • Experience with HMI/SCADA systems and industrial communication protocols (e.g., Modbus, Ethernet/IP).
  • Strong understanding of control theory, instrumentation, and automation standards.

Preferred Qualifications:

  • Master’s degree in Control Systems Engineering or related discipline.
  • Experience with advanced control strategies such as PID tuning, model predictive control, or robotics integration.
  • Familiarity with safety instrumented systems (SIS) and relevant safety standards (e.g., IEC 61508, ISA 84).
  • Knowledge of programming languages such as C/C++ or Python for control system customization.
  • Professional Engineering (PE) license or relevant industry certifications (e.g., Certified Automation Professional).

Responsibilities:

  • Design, develop, and implement control system architectures and software for industrial automation projects.
  • Perform system integration, testing, and commissioning of control hardware and software components.
  • Troubleshoot and resolve control system malfunctions and optimize system performance.
  • Collaborate with electrical, mechanical, and process engineering teams to ensure cohesive system design and operation.
  • Develop and maintain technical documentation, including control system schematics, programming code, and user manuals.
  • Evaluate and recommend new control technologies and methodologies to improve system efficiency and reliability.
  • Provide technical support and training to operations and maintenance personnel on control systems.

Skills:

The required skills enable the Controls Engineer II to design and implement robust control systems that meet operational needs and safety requirements. Proficiency in PLC programming and HMI/SCADA systems is essential for daily development, testing, and troubleshooting activities. Strong analytical and problem-solving skills are applied to diagnose system issues and optimize performance effectively. Preferred skills such as advanced control strategies and programming languages allow the engineer to innovate and customize solutions beyond standard automation practices. Communication and collaboration skills are also vital for working with multidisciplinary teams and providing technical guidance to stakeholders.