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Model Predictive Control Jobs (NOW HIRING)

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Robotic Controls Researcher

Redmond, WA · On-site

$122K - $181K/yr

Responsibilities Conducting collaborative research on developing control algorithms for a wide range of robotics platforms • Development of model predictive control approaches mapping robot ...

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 ...

Milwaukee-Tool

WI · On-site

Knowledge of Advanced control systems, Model Predictive Control.Experience with auto code generation.Working knowledge of with battery, drive, and motor systems.Experience leading technical teams.We ...

Mind Robotics

Controls Engineer

Palo Alto, CA · On-site

$98K - $127K/yr

Experience with whole‑body control, trajectory optimization, or model predictive control on legged or manipulator systems * Familiarity with field‑oriented control (FOC) or other motor control ...

NEURA Robotics

$70K - $91K/yr

Trajectory optimization and model-predictive control pipelines over robot state, contact schedules, ground reaction forces, centroidal momentum, and joint trajectories -- using reduced-order ...

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Model Predictive Control information

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$55K

$96.6K

$131K

How much do model predictive control jobs pay per year?

As of Sep 11, 2026, the average yearly pay for model predictive control in the United States is $96,574.00, according to ZipRecruiter salary data. Most workers in this role earn between $83,500.00 and $108,000.00 per year, depending on experience, location, and employer.

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.
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Model Predictive Control jobs near you
Infographic showing various Model Predictive Control job openings in the United States as of September 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $96,574 per year, or $46.4 per hour.

LEAD APC ENGINEER

Sugar Land, TX • On-site

Yokogawa Electric Corporation
See more jobs at Yokogawa Electric Corporationexternal

$91K - $121K/yr

Full-time

Medical, Dental, Vision, Retirement

Re-posted 5 days ago

Job description

Not just a job, but a career
Yokogawa, award winner for 'Best Asset Monitoring Technology' and 'Best Digital Twin Technology' at the HP Awards, is a leading provider of industrial automation, test and measurement, information systems and industrial services in several industries.
Our aim is to shape a better future for our planet through supporting the energy transition, (bio)technology, artificial intelligence, industrial cybersecurity, etc. We are committed to the United Nations sustainable development goals by utilizing our ability to measure and connect.
About the Team
Our 18,000 employees work in over 60 countries with one corporate mission, to "co-innovate tomorrow". We are looking for dynamic colleagues who share our passion for technology and care for our planet. In return, we offer you great career opportunities to grow yourself in a truly global culture where respect, value creation, collaboration, integrity, and gratitude are highly valued and exhibited in everything we do.
Yokogawa Corporation of America is seeking a highly skilled Lead APC Engineer to develop, implement, and optimize Advanced Process Control (APC) solutions for our industrial automation clients. As a key technical leader, you will be responsible for delivering high-quality APC applications using Yokogawa's suite of advanced process control tools, including PACE, and OpreX Control & Safety Systems. You will work closely with customers to enhance process efficiency, reduce variability, and drive digital transformation initiatives.
Key Responsibilities:
APC Design & Implementation:
  • Develop and deploy model predictive control (MPC) solutions using Yokogawa's PACE and other APC technologies.
  • Conduct dynamic process modeling, simulation, and optimization to improve production efficiency and reduce energy consumption.
  • Implement multivariable control strategies to stabilize operations and optimize key performance indicators (KPIs).

Process Optimization & Support:
  • Analyze plant data to identify areas for improvement and implement real-time optimization (RTO) solutions.
  • Provide performance monitoring, tuning, and troubleshooting support for APC applications.
  • Work closely with DCS and SIS engineers to ensure seamless integration of APC with Yokogawa's CENTUM VP and ProSafe-RS systems.

Customer Engagement & Project Management:
  • Lead APC projects for clients in oil & gas, petrochemical, refining, and chemical industries.
  • Coordinate with process engineers, IT teams, and operations staff to ensure successful deployment of APC solutions.
  • Deliver training and mentorship to customer teams and junior engineers on APC methodologies and best practices.

Innovation & Continuous Improvement:
  • Stay up to date on industry trends, AI-driven process control, and digital transformation technologies.
  • Develop new algorithms, scripts, and workflows to enhance Yokogawa's APC offerings.
  • Contribute to R&D efforts by validating and refining new APC functionalities for Yokogawa products.

Qualifications & Skills:
Education:
  • Bachelor's or Master's degree in Chemical Engineering, Process Control, Electrical Engineering, or a related field.

Experience:
  • 7+ years of experience in Advanced Process Control (APC), preferably in the refining, petrochemical, or energy industries.
  • Strong knowledge of Yokogawa APC solutions or experience with other APC tools such as Aspen DMC+, Honeywell Profit Suite, or Schneider Electric APC.

Technical Expertise:
  • Strong understanding of model predictive control (MPC), real-time optimization (RTO), and multivariable control (MVC).
  • Hands-on experience with DCS systems (Yokogawa CENTUM VP preferred) and industrial communication protocols
  • Knowledge of establishing connectivity to OPC servers.
  • Knowledge of process simulation tools (Aspen HYSYS, gPROMS, or similar).
  • Proficiency in data analysis, scripting (Python, MATLAB, or SQL), and machine learning concepts is a plus.

Soft Skills:
  • Excellent problem-solving, analytical, and troubleshooting skills.
  • Strong leadership and project management abilities.
  • Effective communication and customer-facing skills.

Preferred Qualifications:
  • Experience working with AI-driven process optimization and digital twin technologies.
  • Certifications in process control, industrial automation, or Yokogawa APC solutions.
  • Knowledge of industrial cybersecurity practices in control systems.

Benefits & Growth Opportunities:
  • Competitive salary and performance-based incentives.
  • Comprehensive health, dental, vision, and retirement benefits.
  • Professional development opportunities, including Yokogawa training and certifications.
  • Exposure to cutting-edge industrial automation and digital transformation projects.

Yokogawa is an Equal Opportunity Employer. Yokogawa wants a diverse, equitable and inclusive culture. We will actively recruit, develop, and promote people from a variety of backgrounds who differ in terms of experience, knowledge, thinking styles, perspective, cultural background, and socioeconomic status. We will not discriminate based on race, skin color, age, sex, gender identity and expression, sexual orientation, religion, belief, political opinion, nationality, ethnicity, place of origin, disability, family relations or any other circumstances. Yokogawa values differences and enables everyone to belong, contribute, succeed, and demonstrate their full potential.
Are you being referred to one of our roles? If so, ask your connection at Yokogawa
about our Employee Referral process!

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