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Model Predictive Control Jobs in Dayton, OH (NOW HIRING)

By leveraging expertise in machine learning, algorithms, model-predictive control, and software development, we build tools that support tactical mission planning and execution, autonomous reasoning ...

By leveraging expertise in machine learning, algorithms, model-predictive control, and software development, we build tools that support tactical mission planning and execution, autonomous reasoning ...

By leveraging expertise in machine learning, algorithms, model-predictive control, and software development, we build tools that support tactical mission planning and execution, autonomous reasoning ...

By utilizing the Just-In-Time production model we are able to identify and solve problems ... Perform basic preventive/predictive maintenance. * Participates in improvement activities.

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

Provide the safest possible workplace to our employees by modeling and following all company safety ... Develops and executes preventative and predictive maintenance system to minimize equipment downtime ...

Provide the safest possible workplace to our employees by modeling and following all company safety ... Develops and executes preventative and predictive maintenance system to minimize equipment downtime ...

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Model Predictive Control information

See Dayton, OH salary details

$53.5K

$93.9K

$127.3K

How much do model predictive control jobs pay per year?

As of Aug 22, 2026, the average yearly pay for model predictive control in Dayton, OH is $93,866.00, according to ZipRecruiter salary data. Most workers in this role earn between $81,200.00 and $105,000.00 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 Dayton, OH?

For Model Predictive Control jobs in Dayton, OH, the most frequently searched job titles are:

What cities near Dayton, OH are hiring for Model Predictive Control jobs?

Cities near Dayton, OH with the most Model Predictive Control job openings:

Infographic showing various Model Predictive Control job openings in Dayton, OH 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 $93,866 per year, or $45.1 per hour.

Autonomy Algorithms Senior Software Engineer

STR

Dayton, OH โ€ข On-site, Remote

$134K - $184K/yr

Full-time

Posted 22 days ago


Job description

About the Team:ย 

STR's Analyticsย & C2ย Division develops novel technologies to solve challenging national security problems through advanced analytics. Our team consists of passionate and motivated individuals with degrees in engineering, computer science, mathematics, physics, and data science. We use ourย expertiseย and creativity to take innovative ideas from conception to mature implementationย in order toย improve mission success.ย 

Theย Collaborative Autonomy and Controlย (CAC) Group in the AC2ย Division works toย build software systems that solve critical problems in the areas of uncrewed system autonomy, multi-agent collaboration, resource management, and control. Byย leveragingย expertiseย inย machine learning, algorithms,ย model-predictive control,ย and software development, we build tools thatย supportย tacticalย mission planningย and execution, autonomous reasoning, and more.ย 

The Role:ย 

As an Autonomy Algorithmsย Seniorย Software Engineer,ย you will work as part of a tightly knit team to design, develop, implement, integrate, test, andย demonstrateย advanced algorithms and software systems for autonomous platforms. You will provide technical leadership and mentoring on programs working throughout the software and system development lifecycle, from early prototypes to integrated systems. Your work will develop a diverse set of software tools and applications for mission planning systems, automated control processes, unmanned platforms,ย DevSecOps, and CI/CD pipelines. This position is based in Woburn, MA, Arlington, VA,ย or Dayton, OH,ย and will take advantage of STR's flexible, hybrid environment - when the work does not require use of STR's facilities, you are welcome to work remotely.ย ย 

Who You Are:ย 

  • Ability to obtain a security clearance, for which U.S Citizenship is needed by the U.S government
  • BS in Computer Science or related technical field with 5+ years of experience
  • 3+ years of experience with C++ or Java
  • Full stack development experience but with a heavy focus on backend algorithmic development
  • Proven understanding of data structures, algorithms, concurrency, and code optimization of backend executables
  • Proven ability to develop, implement, integrate, and test autonomy algorithms and software
  • Not interested in Front end UI/UX or database management/interaction
  • Proven ability to work with research scientists to transition complex mathematical algorithmic concepts to software application
  • Proven ability to proactively assume leadership within modest size engineering teams (2-4 engineers) through complete Agile development lifecycle including task definition, delegation, and maintenance
  • Demonstrated success executing industry best practices in areas such as code review, unit testing, test coverage, static analysis, etc., to ensure mature, high quality software products
  • Experience in supporting system/software architecture design at the system and system of systems (SoS) levels
  • Experience utilizing the following:ย 
    • Object-Oriented Programming principles for large scale systems
    • Agile software lifecycle methodologies and tools, such as JIRA, Confluence, Gitlab, static analysis, etc
    • Test-driven development methodologiesย 
  • A demonstrated ability to adopt new languages, libraries, and technologiesย 

Even Better:ย 

  • MS or PhD in Computer Science or related technical field
  • Experience with the following: ย 
    • Collection Orchestration
    • Satellite Constellation Management
    • Containerization and service based architectures
    • Coordinating Electronic Warfare resources
    • Reinforcement learning
    • Agentic AI
    • Experience programming for embedded and physical devices
    • Multi-agent coordination of UxVs
    • MAVLINK or other C2 protocols
    • ROS TAK
    • DevSecOps and CI/CD tool chains
    • Constraint satisfaction algorithmsย 
    • Knowledge representation/ontologies
    • Pythonย 
  • Active Security Clearanceย 

Pay Informationย 

Full-Time Salary Range: $134,000 - $184,000ย 

The salary range listed is based on external market data. Offers are based on factors, such as but not limited to, the candidate's experience, education, training, key skills/critical skills, security clearances, and prevailing market and business conditions.ย