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Model Predictive Control Jobs in Missouri (NOW HIRING)

Pwc

AI Solutions Engineering Delivery Lead

Kansas City, MO · On-site

$100K - $131K/yr

You will work on developing predictive models, conducting statistical analysis, and creating data ... control and continuous improvement of AI solutions, closely collaborating with business ...

Pwc

AI Solutions Engineering Delivery Lead

Saint Louis, MO · On-site

$99K - $131K/yr

You will work on developing predictive models, conducting statistical analysis, and creating data ... control and continuous improvement of AI solutions, closely collaborating with business ...

Deloitte

Manager - ServiceNow

Kansas City, MO · On-site +1

... control, and status reporting with clear key performance indicators, value realization, and ... Orchestrating cross-functional teams and vendors across onshore and offshore models; aligning ...

Next Level Solutions

Senior Business Analyst

Springfield, MO · On-site +1

$78K - $101K/yr

Maintain and manage requirements repository--requirement-level change control including impact ... SQL, Power BI, and Tableau; develop advanced analytics models to forecast demand, capacity, or ...

Schreiber Foods, Inc.

Manufacturing Engineer

Mount Vernon, MO · On-site

$57K - $73K/yr

... integrate predictive maintenance strategies. Collaborate with Maintenance and Reliability ... Define and own manufacturing process control plans. Set up in-process measurement systems. Complete ...

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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 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 are popular job titles related to Model Predictive Control jobs in Missouri? For Model Predictive Control jobs in Missouri, the most frequently searched job titles are:
What job categories do people searching Model Predictive Control jobs in Missouri look for? The top searched job categories for Model Predictive Control jobs in Missouri are:
Model Predictive Control jobs near you
Infographic showing various Model Predictive Control job openings in Missouri as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution.

Senior Consultant - AI Solutions - 1898 & Co

Burns & McDonnell

Kansas City, MO

Full-time

Re-posted 19 days ago

Burns & McDonnell rating

8.7

Company rating: 8.7 out of 10

Based on 50 frontline employees who took The Breakroom Quiz

3rd of 80 rated construction

Job description

At 1898 & Co., we help our clients unlock the power of data and analytics to shape smarter business strategies and drive innovation. Our Business Intelligence & Analytics team works with electric utilities, energy companies, and other critical infrastructure clients to design, implement, and deliver advanced analytics and AI-enabled solutions. As part of Burns & McDonnell, we bring decades of industry expertise and a spirit of innovation to solve some of the most pressing infrastructure challenges of our time.

We are seeking a consultant focused on AI solutions and architecture who is passionate about applying analytics and artificial intelligence to transform utility operations and decision-making. In this role you'll partner with clients to identify high-impact opportunities, shape AI strategies, and collaborate with data scientists, engineers, and business experts to design solutions that transform operations, improve customer experiences, and advance sustainability. You'll bring curiosity, adaptability, and a commitment to continual learning to stay ahead of emerging technologies and their applications in the industry.

What You'll Do

Conduct research into the application of analytics to new domains, with a focus on electric utilities and critical infrastructure.

Apply a pragmatic problem-solving approach to create value while ensuring robustness and data integrity.

Document and summarize findings, develop visualizations, and communicate insights effectively to stakeholders.

Envision and design AI-enabled solutions that address challenges such as grid modernization, asset management, outage prediction, renewable integration, and customer engagement.

Work closely with clients to translate business needs into AI/analytics opportunities and define solution roadmaps.

Collaborate with technical experts to ensure solutions are practical, scalable, and aligned with client goals.

Stay informed on emerging AI technologies and evaluate their impact on utility operations.

Lead workshops and presentations to communicate solution concepts and inspire stakeholder engagement.

Provide leadership, mentoring, and guidance to project teams and junior staff.

Champion a culture of innovation, continuous learning, and exploration of AI's potential.

Thrive in a fast-paced environment with shifting priorities.

Ensure QA/QC process adherence and compliance with company policies, quality standards, and safety requirements.

Perform other duties as assigned.

  • Bachelor's degree in Data Analytics, Computer Science, Engineering, or related field (Master's/PhD preferred). 

    • 7 years of experience in analytics, AI/ML, or utility operations with a strong focus on solution development and strategy.

    • Proficiency with Python and support data and analytics libraries.   

    • Strong familiarity with the electric utility industry, its data domains (AMI, SCADA, GIS, asset/customer systems), and its operational challenges. 

    • Working knowledge of AI and analytics methods (machine learning, predictive modeling, data visualization) with the ability to collaborate effectively with technical experts. 

    • Passion for continual learning and applying new AI/analytics advancements to solve real-world industry challenges. 

    • Strong communication skills with the ability to engage both executives and technical teams. 

  • Consulting or client-facing experience strongly preferred. 

What Burns & McDonnell employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

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About Burns & McDonnell

Sourced by ZipRecruiter

Burns & McDonnell assists clients of all sizes and industries by providing extensive physical services ranging from assessments, integrated security solutions, and large security architecture designs. Services we typically provide include security and safety system design, threat, risk, and vulnerability assessments, security surveys, security master planning, compliance to federal security programs, independent validation and verification of integrated security system operations, management of installation and maintenance, and staff augmentation to develop and implement facility management and protection processes.

Industry

Civil engineering construction

Company size

10,000+ Employees

Headquarters location

Kansas City, MO, US

Year founded

1898

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