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Model Predictive Control Jobs (NOW HIRING)

Covestro

Principal APC Engineer

Baytown, TX · On-site

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

$95K - $130K/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)

Cypress HCM

Control Systems Engineer

Irvine, CA · On-site

$200K - $250K/yr

Lead the design and implementation of control algorithms for medical devices, including closed-loop systems, adaptive control, and model predictive control. * Develop simulation models (e.g., MATLAB ...

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IntelliPro

Control Engineer (Santa Clara)

Santa Clara, CA · On-site

$170K - $230K/yr

Strong expertise in control theory including nonlinear control, model predictive control, and optimal control * Experience with state estimation techniques such as Kalman filters, particle filters ...

Amazon

Applied Scientist, Navigation

San Francisco, CA · On-site

... as model predictive control (MPC)-based trajectory planning. You will develop navigation solutions that seamlessly blend data-driven intelligence with principled control-theoretic guarantees. Our ...

Amazon

Applied Scientist, Navigation

San Francisco, CA · On-site

... as model predictive control (MPC)-based trajectory planning. You will develop navigation solutions that seamlessly blend data-driven intelligence with principled control-theoretic guarantees. Our ...

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All JobsModel Predictive Control Jobs

Model Predictive Control information

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$55K

$96.6K

$131K

How much do model predictive control jobs pay per year?

As of Jul 7, 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 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 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 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.
More about Model Predictive Control jobs
What cities are hiring for Model Predictive Control jobs? Cities with the most Model Predictive Control job openings:
What states have the most Model Predictive Control jobs? States with the most job openings for Model Predictive Control jobs include:
What job categories do people searching Model Predictive Control jobs look for? The top searched job categories for Model Predictive Control jobs are:
Model Predictive Control jobs near you
Infographic showing various Model Predictive Control job openings in the United States as of July 2026, with employment types broken down into 95% Full Time, and 5% Contract. Highlights an 100% In-person job distribution, with an average salary of $96,574 per year, or $46.4 per hour.
Simulation and Control Systems Engineer - Platform Architecture

Simulation and Control Systems Engineer - Platform Architecture

Apple

Cupertino, CA • On-site

Full-time

Posted 27 days ago

Apple rating

8.1

Company rating: 8.1 out of 10

Based on 667 frontline employees who took The Breakroom Quiz

5th of 30 rated technology retailers

Job description

Apple's Platform Architecture team is looking for a Simulation and Control Systems Engineer with a strong software background to help develop advanced thermal and power management algorithms. In this role, you will collaborate with a cross-functional team to design, implement, and validate algorithms that power millions of Apple devices worldwide.
Description
In this role, you will design, implement, debug, and validate control and estimation algorithms for complex thermal and electrical systems. You'll work closely with electrical and thermal engineering teams to interpret system requirements and constraints, and partner with software engineering teams to ensure that control algorithms are integrated in a robust, scalable, and efficient manner.
You will design and execute experiments for modeling and validation, collect and analyze data, and identify potential issues. When challenges arise, you'll be expected to propose thoughtful fixes and architectural decisions to ensure system performance and reliability.
This role offers a unique opportunity to work across hardware and software domains and to contribute directly to the performance of Apple's world-class products.
Minimum Qualifications
BS in Electrical Engineering, Mechanical Engineering, Aerospace Engineering, Robotics, Computer Science or similar degree.
Hands-on experience in control systems development. (Such as modeling, algorithm design, simulation, implementation and/or testing)
Experience in Python or MATLAB.
Experience implementing control algorithms on embedded microcontroller platforms.
Experience with optimization techniques and modern control theory.
Preferred Qualifications
10 years relevant industry experience.
M.S. or Ph.D. in Electrical Engineering, Mechanical Engineering, Aerospace Engineering, Robotics, or Computer Science, with a focus on control systems or robotics, or equivalent professional experience.
Proficiency in C++.
Experience with software engineering workflows, including Git, code review, and CI/CD pipelines.
Strong knowledge of system identification, estimation theory, and statistical learning methods.
Knowledge of optimal and robust control, adaptive control, model predictive control and/or task and trajectory planning.
Ability to communicate complex control and algorithmic concepts clearly to cross-functional hardware and software teams.

What Apple employees say

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Benefits

Hours and flexibility

Workplace

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About Apple

Sourced by ZipRecruiter

Imagine what you could do here! At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Dynamic, intelligent people and inspiring, innovative technologies are the norm here. The people who work here have reinvented entire industries with all Apple Hardware products. The same real passion for innovation that goes into our products also applies to our practices strengthening our dedication to leave the world better than we found it.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Cupertino, CA, US

Year founded

1976

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