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Model Predictive Control Jobs in Downers Grove, IL

Senior AI/ML Engineer

Chicago, IL ยท On-site

$107K - $147K/yr

Build predictive models using large-scale financial, transactional, and behavioral datasets to ... Through our user-friendly tools and intuitive platforms, we empower our members to take control of ...

... control. Qualifications * Education: Bachelor's degree in Data Analytics, Computer Science ... Knowledge of statistical methods and basic predictive modeling techniques. What We Offer * Targeted ...

Senior Data Engineer, gTech Risk

Chicago, IL ยท On-site

$88K - $111K/yr

To ensure gTech's security and agility, the team analyzes gTech business processes to find control ... Develop and maintain the data architecture and predictive models powering gTech's risk graph.

New

Predictive analysis and regression analysis; Root-Cause and Root-Cause Failure Analysis (RCF, RCFA); Fault Tree Analysis; Reliability Modeling and Prediction; Supervisory Control and Data Acquisition ...

ServiceNow Developer

Chicago, IL ยท Remote

$55.75 - $76.50/hr

You will work within an Agile delivery model alongside business analysts, QA, platform ... Code reviews and quality control checks should be undertaken as part of every update set, project ...

ServiceNow Developer

Chicago, IL ยท On-site

$55.75 - $76.50/hr

You will work within an Agile delivery model alongside business analysts, QA, platform ... Code reviews and quality control checks should be undertaken as part of every update set, project ...

ServiceNow Developer

Chicago, IL ยท On-site

$55.75 - $76.50/hr

You will work within an Agile delivery model alongside business analysts, QA, platform ... Code reviews and quality control checks should be undertaken as part of every update set, project ...

Showing results 21-40

Model Predictive Control information

See Downers Grove, IL salary details

$54.9K

$96.3K

$130.7K

How much do model predictive control jobs pay per year?

As of Sep 4, 2026, the average yearly pay for model predictive control in Downers Grove, IL is $96,349.00, according to ZipRecruiter salary data. Most workers in this role earn between $83,300.00 and $107,700.00 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.

What are popular job titles related to Model Predictive Control jobs in Downers Grove, IL?

For Model Predictive Control jobs in Downers Grove, IL, the most frequently searched job titles are:

What job categories do people searching Model Predictive Control jobs in Downers Grove, IL look for?

The top searched job categories for Model Predictive Control jobs in Downers Grove, IL are:

What cities near Downers Grove, IL are hiring for Model Predictive Control jobs?

Cities near Downers Grove, IL with the most Model Predictive Control job openings:

Infographic showing various Model Predictive Control job openings in Downers Grove, IL as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 21% Part Time, 2% Contract, and 1% Nights. Highlights an 95% Physical, 1% Hybrid, and 4% Remote job distribution, with an average salary of $96,349 per year, or $46.3 per hour.

Configuration Management Engineer

Argonne National Laboratory

Lemont, IL โ€ข On-site

$94.49 - $147.40/hr

Other

Re-posted 27 days ago


Job description

The Advanced Photon Source (APS) at Argonne National Laboratory is seeking a Configuration Management Engineer to support the implementation and long-term sustainment of an integrated Configuration Management and Asset Management ecosystem across accelerator systems, beamlines, utilities, and scientific infrastructure. This role will be part of a multidisciplinary engineering and operations team responsible for implementing a modern Computerized Maintenance Management System (CMMS) integrated with a Configuration Database to improve reliability, traceability, and lifecycle management of APS technical assets. The Configuration Management Engineer will help establish and maintain configuration control processes, ensure data integrity across engineering and operational systems, and support the transition toward a data-driven, AI-enabled asset management framework. Following implementation of the CMMS โ€“ Configuration Database strategy, the position will play a critical role in sustaining the system, ensuring configuration integrity, supporting maintenance and engineering workflows, and enabling predictive maintenance and reliability analytics capabilities across the facility.

Key Responsibilities
  • Configuration Management Implementation
    • Support implementation of configuration management processes for APS accelerator systems, beamlines, utilities, and experimental infrastructure.
    • Assist in deploying and integrating the CMMS and Configuration Database platform with existing APS engineering and operational systems.
    • In collaboration with APS operations, define and maintain asset hierarchies, configuration baselines, and system relationships within the CMMS โ€“ Configuration Database ecosystem.
    • Ensure configuration traceability between physical assets, engineering documentation, maintenance records, and operational data.
  • System Integration & Data Management
    • Work with engineering, IT, and operations teams to integrate CMMS โ€“ Configuration Database platforms with controls systems and operational data historians, engineering document management systems, component and asset databases, reliability and analytics platforms.
    • Support development and maintenance of data governance and master data management practices.
    • Ensure data quality, consistency, and configuration integrity across systems.
  • Configuration Control & Lifecycle Management
    • Support engineering change control processes and configuration baseline management.
    • Maintain configuration documentation and system relationships throughout the asset lifecycle.
    • Assist with compliance with DOE, Argonne, and APS configuration management and quality assurance requirements.
    • Provide configuration management support during system upgrades, modifications, and operational changes.
  • Reliability & Analytics
    • Collaborate with reliability engineering and operations teams to enable data-driven maintenance strategies.
    • Support analytics initiatives related to predictive maintenance, reliability metrics (MTBF/MTTR), and asset performance management.
    • Assist in developing dashboards and reporting frameworks to support operational decision-making.
  • Long-Term Sustainment
    • Provide ongoing support and stewardship for the CMMS โ€“ Configuration Database ecosystem after deployment.
    • Assist in maintaining system documentation, user training materials, and operational procedures.
    • Identify opportunities for continuous improvement in asset management, maintenance workflows, and configuration control practices.
    • May be required to perform other duties as assigned.
Position Requirements
  • Bachelors and 5+ yearsโ€™ experience, Masters and 3+ yearsโ€™ experience, PhD and 0+ yearsโ€™ experience, or equivalent Degree in engineering, systems engineering, engineering physics, computer science, or a related technical field.
  • 5+ years of experience in configuration management, asset management, systems engineering, or technical data management.
  • Experience supporting complex technical systems such as scientific facilities, industrial plants, utilities, or large engineering infrastructures.
  • Familiarity with configuration management principles and lifecycle asset management practices.
  • Experience working with engineering databases, asset management systems, or CMMS platforms.
  • Strong analytical, organizational, and documentation skills.
  • Ability to model Argonneโ€™s core values of impact, safety, respect, integrity, and teamwork.
  • Interpersonal skills, oral and written communication skills, and ability to interact with people at all levels both within and outside the laboratory.
Preferred Knowledge, Skills, and Experience
  • Experience with CMMS platforms (e.g., Maximo, SAP PM, Infor EAM, MaintainX, or similar systems).
  • Familiarity with configuration databases, digital engineering environments, or PLM systems.
  • Experience integrating engineering systems with operational data sources or historians.
  • Knowledge of reliability engineering concepts, including MTBF/MTTR and predictive maintenance.
  • Experience working within DOE laboratories, large research facilities, or regulated engineering environments.
  • Familiarity with data governance, APIs, or system integration architectures.

The expected hiring range for this position is $94,486.00 - $147,398.94. Please note that the pay range information is a general guideline only. The pay offered to a selected candidate will be determined based on factors such as, but not limited to, the scope and responsibilities of the position, the qualifications of the selected candidate, business considerations, internal equity, and external market pay for comparable jobs.

comprehensive benefits are part of the total rewards package.

Argonne is an equal employment opportunity employer and is committed to a safe and welcoming workplace that fosters collaborative scientific discovery and innovation. All Argonne offers of employment are contingent upon a background check that includes an assessment of criminal conviction history conducted on an individualized and case-by-case basis. Public employees may also be required to obtain a government access authorization that involves additional background check requirements. Failure to obtain or maintain such government access authorization could result in the withdrawal of a job offer or future termination of employment.

Argonne encourages everyone to apply for employment. Argonne is committed to nondiscrimination and considers all qualified applicants for employment without regard to any characteristic protected by law.

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