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Model Predictive Control Jobs (NOW HIRING)

Senior APC Engineer

Baytown, TX · On-site

$95.10K - $130.70K/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)

Identifyand initiate projects in the fields ofexpertise(Dynamic Modeling, Operator Training Simulators, Advanced Control and Model Predictive Control as well as multivariate data analysis)

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 ...

In this role, you will architect sophisticated control systems using Model Predictive Control (MPC) and identify the dynamic parameters of our vehicles. What You'll Do * Design, implement, and ...

... 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 ...

Experience with model predictive control is a plus. Ideal Candidate Profile The ideal candidate is a well-rounded robotics engineer who can combine software, sensing, controls, and robot integration ...

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 ...

In this role, you will architect sophisticated control systems using Model Predictive Control (MPC) and identify the dynamic parameters of our vehicles. What You'll Do * Design, implement, and ...

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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 Jun 3, 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 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.

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 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 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:
Controls & Modeling Engineer (Senior - Principal) - Advanced Automation

Controls & Modeling Engineer (Senior - Principal) - Advanced Automation

Halliburton

Houston, TX • On-site, Remote

$92.60K - $122.20K/yr

Full-time

Posted 16 days ago


Halliburton rating

7.2

Company rating: 7.2 out of 10

Based on 122 frontline employees who took The Breakroom Quiz

260th of 351 rated engineering


Job description

We are looking for the right people — people who want to innovate, achieve, grow and lead. We attract and retain the best talent by investing in our employees and empowering them to develop themselves and their careers. Experience the challenges, rewards and opportunity of working for one of the world’s largest providers of products and services to the global energy industry.

About Sperry Drilling

Sperry Drilling delivers industry-leading Measurement-While-Drilling (MWD), Logging-While-Drilling (LWD), and Rotary Steerable System (RSS) technologies that help operators drill safer, faster, and more precisely. Through advanced downhole tools, real-time data acquisition, and reliability-driven engineering, Sperry enables customers to maximize well placement, efficiency, and reservoir understanding in every drilling environment.

About the Role

The Controls & Modeling Engineer advances research and development of next-generation automation, controls, robotics, and intelligent systems technologies within the Advanced Controls COE.

This role focus on rigorous application of advanced control theory, dynamic modeling, estimation, optimization, machine learning, and agentic AI to high-value engineering problems.

Work spans early-stage concept generation, algorithm development, simulation and validation, prototype implementation, and transition of emerging technologies into deployable workflows and systems.

This position contributes to strategic R&D initiatives with direct commercial relevance. Scope includes development of physics-based and data-driven methods for automation, operational decision support, autonomous and semi-autonomous systems, and model-based performance improvement. Close collaboration with multidisciplinary teams across engineering, software, digital, and operations.


Key Responsibilities

  • Develop and evaluate agentic AI systems that combine reasoning, tools, data, and simulation assets to enable advanced technical analysis, automation, and human-in-the-loop decision making. 
  • Integrate large language models (LLMs), retrieval-augmented systems, and AI agents with controls, modeling, and optimization frameworks. 
  • Develop machine learning, data analytics, and hybrid physics-AI approaches to improve system performance, automation, and operational efficiency. 
  • Develop software tools, workflows, orchestration pipelines, and visualization capabilities to support AI-enabled engineering and operations. 
  • Conduct research and development in advanced controls, robotics, dynamic modeling, and automation for complex engineering systems. 
  • Design & apply advanced control techniques including adaptive, nonlinear, robust, optimal, and model predictive control (MPC). 
  • Develop and validate dynamic models, simulations, and system identification methodologies. 
  • Collaborate with multidisciplinary teams across engineering, software, data science, and operations. 
  • Contribute to technical innovation through patents, publications, conferences, and internal programs. 
Qualifications

Required

  • PhD or equivalent experience in a relevant engineering or scientific discipline with emphasis on controls, dynamic systems, automation, machine learning, or intelligent systems; or equivalent R&D experience. 
  • Experience with agentic AI, LLM-based workflows, orchestration frameworks, or tool-using AI agents applied to scientific, industrial, or engineering use cases. 
  • Deep knowledge of control theory, including modern control, optimal control, Model Predictive Control (MPC), and system dynamics. 
  • Knowledge of robotics, mechatronics, high‑DoF systems, path planning, and dynamic modeling. 
  • Strong technical communication and collaboration skills. 

Preferred

  • Ability to build data pipelines, workflows, and analytical tools for AI/ML tool chain which includes data cleaning, feature extraction, optimization, and insight generation. 
  • Strong programming skills in MATLAB, Python, C/C++, C#, Java, or similar languages. 
  • Create dashboards and use data visualization tools such as Python, or JavaScript Typescript frameworks. 
  • Ability to design, analyze, and troubleshoot control systems, sensors, actuators, pumps, VFDs, and automation hardware. 
  • Strong capability to read and interpret electrical schematics, mechanical drawings, P&IDs, flow charts, and cause‑and‑effect diagrams.  

Candidates exceeding minimum requirements may be considered for higher-level positions based on experience, additional qualifications, and business needs. Career progression ranges Controls & Modeling Engineer Senior to Controls & Modeling Engineer Principal. 

World Class Benefits

At Halliburton, we’re committed to supporting you and your family with a comprehensive and affordable benefits package that covers your physical, emotional, financial, and parental needs — now and in the future. When you join our team, you’ll gain access to a wide range of programs designed to help you thrive at work and at home.

Click here to review a summary of the benefits available once you join.

Core Competencies

Advanced Control Systems | Control Theory & System Identification | Robotics & Autonomous Systems | High DoF Systems & Path Planning | Modeling & Simulation | Control + Machine Learning | Data Analytics + Engineering | Neural Networks & Bayesian Methods | MATLAB/Simulink & Python | Dynamic Systems & Optimization | Robotics + Control | Theory + Practical Deployment | Field Implementation Experience | Cross-Functional Collaboration | Innovation & Technology Development

Halliburton is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, disability, genetic information, pregnancy, citizenship, marital status, sex/gender, sexual preference/ orientation, gender identity, age, veteran status, national origin, or any other status protected by law or regulation.

Location

3000 N. Sam Houston Parkway E., Houston, Texas, 77032, United States

Job Details

Requisition Number: 207457  
Experience Level: Experienced Hire 
Job Family: Engineering/Science/Technology 
Product Service Line: Sperry Drilling Svcs   
Full Time / Part Time: Full Time

Additional Locations for this position: 

Compensation Information
Compensation is competitive and commensurate with experience.


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About Halliburton

Sourced by ZipRecruiter

Halliburton, headquartered in Houston, TX, US, is a world-renowned corporation in the oilfield services industry. Established in 1919, the company has made significant inroads in the energy sector, playing a pivotal role in oil and gas explorations across the globe. One can visit their official website, halliburton.com, to learn more about their business operations, products, and services. Halliburton specializes in a broad spectrum of services including locating hydrocarbons, managing geological data, drilling and formation evaluation, well construction and completion, and optimizing production throughout the life of the field. Halliburton’s mission is to maximize the value of oil and gas assets.

Industry

Health care and social assistance

Company size

10,000+ Employees

Headquarters location

Houston, TX, US