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Model Predictive Control Jobs in Alabama (NOW HIRING)

Develop and validate dynamic process models using plant data and first-principles simulation techniques * Configure and tune multivariable predictive controllers and associated control parameters

Experience with advanced process control and optimization, such as soft sensors, model predictive control, Bayesian optimization, and design of experiments. * Experience with deep learning frameworks ...

Ability to use advanced statistical and mathematical software to perform descriptive, predictive ... Familiarity with software version control systems, such as Git CERTIFICATES, LICENSES ...

Senior Thermal Engineer

Huntsville, AL · On-site

$126K - $167K/yr

... control center. As the world enters an era of strategic competition, Anduril is committed to ... Validate models with test data; develop predictive ablation and erosion models. * Define sub-scale ...

... access control, and Splunk for network logging and analysis. The ideal candidate will have a ... Utilize Ekahau software to create predictive models and heatmaps for wireless network performance

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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 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.
What are popular job titles related to Model Predictive Control jobs in Alabama? For Model Predictive Control jobs in Alabama, the most frequently searched job titles are:
What job categories do people searching Model Predictive Control jobs in Alabama look for? The top searched job categories for Model Predictive Control jobs in Alabama are:
What cities in Alabama are hiring for Model Predictive Control jobs? Cities in Alabama with the most Model Predictive Control job openings:
Infographic showing various Model Predictive Control job openings in Alabama as of July 2026, with employment types broken down into 91% Full Time, and 9% Contract. Highlights an 100% In-person job distribution.
Advanced Process Control (APC) Engineer

Advanced Process Control (APC) Engineer

Andritz

Other

Posted yesterday


Andritz rating

8.2

Company rating: 8.2 out of 10

Based on 15 frontline employees who took The Breakroom Quiz

106th of 430 rated machine equipment manufacturers


Job description

Every day, ANDRITZ continues to deliver successful innovative solutions to our customers globally. Why are we so successful? Because we are passionate and love what we do! We are at the forefront of future engineering technologies, with solutions that ensure the success of our clients in key industries that are shaping the future of the world we live in.

ANDRITZ has an immediate opportunity for a skilled Advanced Process Control (APC) Engineer to support the delivery of advanced automation and digitalization solutions across complex industrial environments. In this role, you will work collaboratively with multidisciplinary project teams to optimize customer operations through the design and application of advanced process control technologies, including model predictive control, real-time optimization (RTO), data analytics, and digital twins.
You will play a key role in evaluating process performance, developing and implementing control strategies, and supporting commissioning and continuous improvement initiatives, while ensuring alignment with technical standards, safety requirements, and customer expectations. This position is ideal for a technically strong engineer who thrives in dynamic project environments and is passionate about driving measurable performance improvements.
What You Will Be Doing

Here's an overview of your responsibilities and how you can leverage your expertise:

  • Evaluate operating processes to identify opportunities for optimization, efficiency gains, and variability reduction
  • Design and implement advanced process control (APC) solutions, including control strategies and optimization applications
  • Develop and validate dynamic process models using plant data and first-principles simulation techniques
  • Configure and tune multivariable predictive controllers and associated control parameters
  • Collect, analyze, and interpret engineering and operational data to support model development and optimization strategies
  • Collaborate with control room operators, process engineers, and instrumentation teams to complete commissioning and control response testing
  • Provide commissioning, start-up, and troubleshooting support for deployed APC applications
  • Execute simulation and acceptance testing for large-scale optimization projects to ensure system performance and reliability
  • Monitor application performance and recommend continuous improvements to sustain optimization benefits over time
  • Prepare and maintain technical documentation, including control strategies, test plans, and commissioning reports
  • Support proposal development and identify opportunities for expanded automation and digitalization solutions
  • Adhere to company safety standards, including the ANDRITZ Life-Saving Rules, and promote a strong safety culture
  • Demonstrate and reinforce #1ANDRITZway core values and behaviors in all aspects of work


What We're Looking For

When selecting candidates, we will be looking for the following essential skills, abilities, and experience:

  • Bachelor's degree in Electrical, Mechatronics, Computer, Chemical, Engineering Physics, or Mining Engineering
  • Minimum of five (5) years' experience in industrial automation and/or advanced process control (APC)
  • Hands-on experience with control systems, including DCS/PLC environments and system troubleshooting
  • Strong understanding of advanced process control concepts, including model predictive control (MPC) and loop tuning
  • Proven ability to analyze complex process data and translate insights into effective control strategies
  • Strong problem-solving skills and ability to work independently while contributing to team objectives
  • Excellent interpersonal, verbal, and written communication skills
  • Ability and willingness to travel domestically and internationally to support commissioning and site activities
  • Fluency in English is required; Arabic language skills are a strong asset


Nice to Have

  • Experience in mining, mineral processing, or other heavy industrial process environments
  • Knowledge of predictive control theory and experience with industrial APC platforms
  • Experience with industrial process simulation
  • Familiarity with major control platforms (e.g., Yokogawa, Siemens, Rockwell/Allen-Bradley, ABB, Emerson, Honeywell)
  • Proficiency with Python, R, or SQL
  • Experience in consulting engineering environments
  • Instrumentation and electrical troubleshooting experience
  • Commissioning, construction, and start-up experience


Language & Location Requirements

  • Fluency in English is required
  • Arabic language skills are a strong asset
  • Position based in EMEA, with travel to customer sites as required

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, or disability.


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