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Model Predictive Control Jobs in Chicago, IL (NOW HIRING)

Jobtailor

Data Scientist

Chicago, IL · On-site

$120 - $160/hr

Statistical Modeling * Exploratory Data Analysis * Predictive Analytics * Prescriptive Analytics * Data Mining * Cloud Computing * Version Control (Git) * Database Technologies (SQL, NoSQL) Soft ...

Munich Re

Data Scientist

Chicago, IL · On-site +1

We focus on developing and maintaining predictive models that support all domains across the ... version control, and agile frameworks using tools like Azure DevOps. Skills / Knowledge ...

Lightspeed

AI & Machine Learning Engineer

Northbrook, IL · On-site

$100 - $130/hr

... deploy ML models for robotic control, quality prediction, and process optimization * Develop reinforcement learning and imitation learning systems for robot task planning * Build predictive ...

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All JobsModel Predictive Control JobsModel Predictive Control Jobs in Chicago, IL

Model Predictive Control information

See Chicago, IL salary details

$56.7K

$99.5K

$134.9K

How much do model predictive control jobs pay per year?

As of Aug 22, 2026, the average yearly pay for model predictive control in Chicago, IL is $99,485.00, according to ZipRecruiter salary data. Most workers in this role earn between $86,000.00 and $111,300.00 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 Chicago, IL?

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

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

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

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

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

Model Predictive Control jobs near you
Infographic showing various Model Predictive Control job openings in Chicago, IL as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $99,485 per year, or $47.8 per hour.

Principal Sci, R&D - Ingredient Technology

Kraft Heinz Company

Glenview, IL • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 10 days ago

Kraft Heinz rating

7.0

Company rating: 7.0 out of 10

Based on 122 frontline employees who took The Breakroom Quiz

229th of 442 rated food and drinks producers

Job description

Investigate relationships or solve technical problems, as a scientific professional specializing in research, possibly for a specific application or within a specific branch of science. Independently evaluate, select, and apply standard engineering and scientific techniques, processes, and criteria.Job Description
Principal Scientist, R&D - Ingredient Technology (Fats & Emulsions)
Job Summary:
The Kraft Heinz Next Generation Ingredients R&D team is seeking an experienced scientist in ingredient technology and food system development to join the team in Glenview, IL. In this role, you will lead the discovery, development, and scale-up of new ingredient technologies and product concepts, with a core emphasis on lipid-containing food systems where fat functionality and stability drive product performance and shelf life.
You will translate emerging ingredient, processing, and modeling capabilities into practical solutions for the North American portfolio, particularly in:
  • Oil-in-water emulsions (e.g., mayonnaise and salad dressing-type systems), where performance depends on interfacial behavior and emulsion stability

  • Dairy fat systems in processed cheese and cream cheese, where fat-protein-salt-water interactions and structure drive texture, melt, and quality

Success requires strong ingredient science fundamentals and the ability to operate across laboratory and business settings. You will strengthen predictive control of lipid functionality and shelf-life (especially oxidative quality in cleaner-label systems).
Key Responsibilities:
  • Lead lipid-driven ingredient technology initiatives by framing hypotheses and failure modes, then converting mechanistic understanding into formulation and process options for emulsions and dairy fat applications.

  • Identify and prioritize ingredient technology platforms across the North American portfolio using technology landscaping, literature review, and structured scoping, with focus on fats/oils functionality, emulsion performance, and oxidative stability.

  • Design and execute experimental plans (including stability and accelerated shelf-life); analyze data, develop recommendations, and assess technical risk-distinguishing physical instability (e.g., phase separation) from chemical instability (e.g., oxidation).

  • Apply ingredient science fundamentals to evaluate ingredient interactions, stability, and performance in complex food systems-emphasizing interfaces, fat-protein interactions, salt/water effects, and pro-oxidant drivers.

  • Leverage analytical, modeling, and digital tools to improve experimental efficiency and generate practical formulation and process guidance.

  • Build team capability through mentoring and reusable playbooks for experimental design, troubleshooting, and knowledge capture in emulsion stability and lipid oxidation risk.

  • Build and lead external research collaborations (universities, suppliers, startups, and industry partners) to validate emerging technologies and inform internal direction.

  • Lead cross-functional technical workstreams with key stakeholders (e.g., marketing, operations, quality, regulatory) to advance research and innovation where lipid chemistry or fat-structure stability drives quality or shelf-life risk.

  • Anticipate portfolio needs by proposing technology strategies, value hypotheses, and prioritized learning plans with decision points.

  • Define scalable application pathways from bench to commercial scale, including prototyping and scale-up trials.

Requirements:
  • Bachelor's in Food Science, Chemistry, Biochemistry, Molecular Biology, Dairy Science, Food Chemistry, or related fields. (Master's or PhD preferred)

  • Minimum experience: 6 years (BS), 5 years (MS), or 4 years (PhD).

  • Strong background in ingredient science and ingredient technology development with depth in lipid-containing systems and the ability to diagnose and improve fat-driven performance and shelf-life.

  • Experience leading experiments at bench and pilot scale. Experience running trials in a plant setting is preferred.

  • Demonstrated ability to characterize ingredients and evaluate interactions using appropriate analytical and modeling approaches to assess performance across complex systems.

  • Knowledge of food industry trends, consumer preferences, and regulatory requirements, including experience navigating select cleaner-label programs and ingredient substitution within complex food systems.

  • Working knowledge of lipid chemistry and degradation pathways (e.g., oxidation) and their impact on product quality during shelf life.

  • Excellent communication, collaboration, and stakeholder leadership skills, with the ability to lead technically ambiguous cross-functional initiatives and communicate effectively with both technical and nontechnical audiences.

  • Demonstrated ability to scale technical capability through mentoring and by creating reusable guidance (e.g., playbooks, troubleshooting frameworks, experimental templates) that improves consistency and speed across multiple projects.

  • Ability to prioritize effectively, navigate ambiguity, and set technical direction by translating signals into hypotheses, learning agendas, and decision-ready recommendations.

  • Experience designing shelf-life and accelerated shelf-life studies, with familiarity in analytical, modeling, or AI-enabled tools that strengthen predictive understanding. Experience assessing oxidation is preferred-especially in systems without antioxidants and preservatives.

  • Demonstrated ability to establish and lead collaborative research with universities, suppliers, startups, and industry partners.

Our Total Rewards philosophy is to provide a meaningful and flexible spectrum of programs that equitably support our diverse workforce and their families and complement Kraft Heinz' strategy and values.
New Hire Base Salary Range:
$104,200.00 - $130,200.00
Bonus: This position is eligible for a performance-based bonus as provided by the plan terms and governing documents.
The compensation offered will take into account internal equity and may vary depending on the candidate's geographic region, job-related knowledge, skills, and experience among other factors
Benefits: Coverage for employees (and their eligible dependents) through affordable access to healthcare, protection, and saving for the future, we offer plans tailored to meet you and your family's needs. Coverage for benefits will be in accordance with the terms and conditions of the applicable plans and associated governing plan documents.
Wellbeing: We offer events, resources, and learning opportunities that inspire a physical, social, emotional, and financial well-being lifestyle for our employees and their families.
You'll be able to participate in a variety of benefits and wellbeing programs that may vary by role, country, region, union status, and other employment status factors, for example:
  • Physical - Medical, Prescription Drug, Dental, Vision, Screenings/Assessments
  • Social - Paid Time Off, Company Holidays, Leave of Absence, Flexible Work Arrangements, Recognition, Training
  • Emotional - Employee Assistance Program , Wellbeing Programs, Family Support Programs
  • Financial - 401k, Life, Accidental Death & Dismemberment, Disability

Location(s)
Glenview R&D Center
Kraft Heinz is an Equal Opportunity Employer - Underrepresented Ethnic Minority Groups/Women/Veterans/Individuals with Disabilities/Sexual Orientation/Gender Identity and other protected classes. In order to ensure reasonable accommodation for protected individuals, applicants that require accommodation in the job application process may contact NAZTAOps@kraftheinz.com for assistance.

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