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Model Predictive Control Jobs in Ontario, CA (NOW HIRING)

Cypress HCM

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 ...

Autodesk

Data Scientist, FP&A Solutions

Ontario, CA · On-site +1

Develop predictive models for areas such as revenue, expenses, headcount, bookings, customer ... CD, code review, and version control * Experience working in a large, global, or matrixed ...

VSolvit

DATA SCIENTIST II

Norco, CA · On-site

$115K - $130K/yr

Develop, implement, and maintain predictive models and machine learning algorithms * Collaborate ... Experience with DevOps practices and version control (Git, GitHub) * Strong problem-solving skills ...

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All JobsModel Predictive Control JobsModel Predictive Control Jobs in Ontario, CA

Model Predictive Control information

See Ontario, CA salary details

$56K

$98.3K

$133.3K

How much do model predictive control jobs pay per year?

As of Sep 11, 2026, the average yearly pay for model predictive control in Ontario, CA is $98,258.00, according to ZipRecruiter salary data. Most workers in this role earn between $85,000.00 and $109,900.00 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 Ontario, CA?

For Model Predictive Control jobs in Ontario, CA, the most frequently searched job titles are:

What job categories do people searching Model Predictive Control jobs in Ontario, CA look for?

The top searched job categories for Model Predictive Control jobs in Ontario, CA are:

What cities near Ontario, CA are hiring for Model Predictive Control jobs?

Cities near Ontario, CA with the most Model Predictive Control job openings:

Model Predictive Control jobs near you
Infographic showing various Model Predictive Control job openings in Ontario, CA as of August 2026, with employment types broken down into 1% As Needed, 72% Full Time, 23% Part Time, 3% Contract, and 1% Nights. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution, with an average salary of $98,258 per year, or $47.2 per hour.

Control Systems Engineer

Irvine, CA • On-site

Cypress HCM
Recruiting and Staffing Services • 51 - 200 employees
Learn more about Cypress HCMexternal

$200K - $250K/yr

Full-time

Re-posted 13 days ago

Job description

A top medical device client is seeking a highly experienced, direct hire Control Systems Engineer to lead the design and development of advanced control algorithms for life-saving and life-enhancing medical technologies in Irvine, CA. This is a senior-level role within our R&D Algorithm Development team, requiring deep expertise in control theory, signal processing, physiological systems, and algorithm development for medical device innovation. This is a critical role in shaping the future of intelligent, closed-loop medical systems that improve patient outcomes through precision, automation, and real-time responsiveness.
 
Key Responsibilities:
  1. Apply control engineering, scientific, mathematical, signal processing, and human physiology experience to develop algorithms for critical care patient monitoring and drug delivery products, with specific focus on system automation and closed-loop control.
  2. Lead the design and implementation of control algorithms for medical devices, including closed-loop systems, adaptive control, and model predictive control.
  3. Develop simulation models (e.g., MATLAB/Simulink) to validate control strategies and optimize system performance.
  4. Analyze physiological signals and sensor data to inform algorithm design and improve device responsiveness.
  5. Lead research and feasibility of new concepts, conduct animal studies and clinical data collection, analyze and interpret clinical data, draw conclusions and prepare final reports and presentations.
  6. Conduct verification and validation testing in accordance with FDA and ISO standards.
  7. Support regulatory submissions by documenting algorithm design, performance, and safety considerations.
  8. Guide and mentor engineers on new and emerging technologies and projects.
 
Requirements:
  1. A bachelor’s degree in an Engineering or Scientific field with a minimum of 12 years of experience is required. 
    1. Or a master’s degree in an Engineering or Scientific field with a minimum of 11 years of experience is required. 
    2. Or a PhD or equivalent in an Engineering or Scientific field with a minimum of 8 years of experience is required. PhD highly preferred.
  2. Recognized as an expert within the field of Control Engineering. 
  3. Expert knowledge and understanding of principles, theories, and concepts of control engineering and system dynamics.
  4. Expert knowledge in signal processing, system identification, mathematical modeling and algorithm development. 
  5. Demonstrated proficiency in design, optimization, and validation of control systems and algorithms.
  6. Strong experience with real-time signals, systems and sensors integration.
  7. Proficiency in MATLAB/Simulink and C/C++ for embedded systems. Real-time implementation and integration of control algorithms.
  8. Strong background in human physiology and anatomy with specific knowledge of cardiovascular hemodynamics and vital signs parameters. Experience with physiological waveforms and parameters.
  9. Experience in modeling of the pharmacokinetics and dynamics of drugs.
  10. Experience with design and implementation of physiologic closed-loop controlled medical devices, such as insulin delivery systems, mechanical ventilators and anesthesia delivery systems.
  11. Experience with FDA design controls and IEC software lifecycle processes.
  12. Knowledge of machine learning and AI techniques applied to control systems.
  13. Requires a high-energy individual who has excellent teamwork, partnering, and negotiation skills.
  14. Strong communication skills are needed to facilitate working with BD teams and executives, third parties, physician collaborators and principal investigators.

 Salary of $200,000 to $250,000 annually + bonus and stock options
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About Cypress HCM

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We deliver consistently superior recruiting by virtue of trusting, communicative relationships with companies and candidates alike. From Fortune 100s to startups, clients lean on us to fulfill their range of needs from contract to full-time positions. With an intimate knowledge of the industries we serve, a keen sense of what makes for high-performing talent in any role, and shared sense of urgency, our clients will tell you: your solution begins here.

Industry

Recruiting and staffing services

Company size

51 - 200 Employees

Headquarters location

Walnut Creek, CA, US

Year founded

2005

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