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Model Predictive Control Jobs (NOW HIRING)

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 ...

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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 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.
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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.
Principal Applied Scientist, Robotics

Principal Applied Scientist, Robotics

Amazon

North Reading, MA • On-site

Full-time

Posted 17 days ago

Amazon rating

7.4

Company rating: 7.4 out of 10

Based on 6,930 frontline employees who took The Breakroom Quiz

6th of 39 rated national retailers

Job description

We are seeking a Principal Applied Scientist to help develop the next generation of advanced robotics systems that will transform automation at Amazon's scale. We're building revolutionary robotic systems that combine cutting-edge AI, sophisticated control systems, and advanced mechanical design to create adaptable automation solutions capable of working safely alongside humans in dynamic environments. This is a unique opportunity to shape the future of robotics and automation at an unprecedented scale, working with world-class teams pushing the boundaries of what's possible in robotic dexterous manipulation, locomotion, and human-robot interaction.

This role presents an opportunity to shape the future of robotics through innovative applications of deep learning and large language models.
We leverage advanced robotics, machine learning, and artificial intelligence to solve complex operational challenges at an unprecedented scale. Our fleet of robots operates across hundreds of facilities worldwide, working in sophisticated coordination to fulfill our mission of customer excellence.


The ideal candidate will contribute to research that bridges the gap between theoretical advancement and practical implementation in robotics. You will be part of a team that's revolutionizing how robots learn, adapt, and interact with their environment.
Join us in building the next generation of intelligent robotics systems that will transform the future of automation and human-robot collaboration.
Key job responsibilities
- Define and drive the long-term scientific roadmap for whole body control and dexterous manipulation, working with autonomy and delivering artifacts that set the standard for scientific and engineering excellence
- Serve as the primary technical authority on whole body control methods - including reinforcement learning, imitation learning, hierarchical quadratic programming, and model-predictive control - across the organization
- Identify and tackle intrinsically hard, open-ended research problems in loco-manipulation, acquiring expertise as needed and proposing innovative solutions that span multiple teams
- Collaborate with hardware and robotics leads to co-design systems for loco-manipulation, ensuring science solutions are grounded in real-world deployment constraints
- Represent scientific capabilities to senior leadership and external partners; communicate complex technical concepts to both technical and non-technical audiences
- Mentor and develop a community of Applied Scientists and engineers, raising the scientific bar across the organization

What Amazon employees say

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Benefits

Hours and flexibility

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About Amazon

Sourced by ZipRecruiter

Amazon.com, Inc., commonly known as Amazon, is an American multinational technology company. It was founded by Jeff Bezos in 1994 and initially started as an online marketplace for books. Since then, Amazon has expanded its operations and become one of the largest e-commerce companies in the world. Amazon's primary business is its online retail platform, where customers can purchase a vast array of products, including electronics, clothing, books, home goods, and much more. The company offers a convenient and user-friendly shopping experience, with features such as fast shipping, customer reviews, and personalized recommendations. In addition to its e-commerce platform, Amazon has diversified its business into various other areas. One of its notable ventures is Amazon Web Services (AWS), a comprehensive cloud computing platform that provides services such as storage, compute power, and database management to individuals and businesses. AWS has become a leader in the cloud computing industry, powering many websites and applications worldwide. Amazon has also developed its own consumer electronics, including the popular Amazon Kindle e-reader, Fire tablets, Fire TV streaming devices, and the Alexa-powered Echo smart speakers. The Alexa voice assistant, integrated into these devices, allows users to interact with their devices using voice commands, perform tasks, and access information. Furthermore, Amazon has expanded into media and entertainment. It operates Prime Video, a streaming service that offers a wide range of movies, TV shows, and original content. Amazon Music provides a platform for streaming and purchasing digital music, while Audible offers audiobooks and other audio content. The company's commitment to customer satisfaction and convenience is demonstrated by its membership program, Amazon Prime. Prime members receive various benefits, including free two-day shipping, access to streaming services, exclusive deals, and more.

Industry

It services, book publishers, retail, real estate and computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Seattle, WA, US

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