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Model Predictive Control Jobs in Kentucky (NOW HIRING)

$96 - $110/hr

Integrate LLMs, predictive models, business logic, and behavioural data into recommendation ... control, testing, modular design, and production monitoring * Experience integrating machine ...

$128 - $206/hr

Export Control/ITAR:* Certain roles may be subject to U.S. export control laws, requiring U.S ... Productionize **reasoning models, vision-language models (VLMs), and multimodal AI systems** that ...

$220 - $292/hr

Demonstrated experience in guidance, navigation, and control (GNC); trajectory optimization; and/or the development of predictive models for vehicle dynamics and weapon system effectiveness (e.g., 6 ...

$220 - $292/hr

Demonstrated experience in guidance, navigation, and control (GNC); trajectory optimization; and/or the development of predictive models for vehicle dynamics and weapon system effectiveness (e.g., 6 ...

New

$140 - $210/hr

... control plane is the layer that makes that possible. It deploys the agents, it deploys the models ... DataRobot empowers practitioners to deliver predictive and generative AI, and enables leaders to ...

New

$146 - $194/hr

Demonstrated experience in guidance, navigation, and control (GNC); trajectory optimization; and/or the development of predictive models for vehicle dynamics and weapon system effectiveness (e.g., 6 ...

Grading and drainage design and stormwater modeling experience. * * Erosion and sediment control ... predictive models, spreadsheets, and tools. * Demonstrated commitment to safety, ethical decision ...

Grading and drainage design and stormwater modeling experience. * * Erosion and sediment control ... predictive models, spreadsheets, and tools. * Demonstrated commitment to safety, ethical ...

$113 - $135/hr

... predictive algorithms preferably in the risk domain. We'd love to chat if you have ... Minimum 3+ years of experience in end to end fraud risk control strategy experience within relevant ...

$128 - $209/hr

ETM/TruRisk, CSAM (Asset Management), QPM (Patch Management) and QPA (Policy Control/Audit, EASM ... Familiarity with AI, machine learning, and predictive risk modeling* Experience using Microsoft ...

... and predictive analytics * Perform feature engineering, experimentation, model evaluation ... Ensure adherence to SDLC standards, documentation, version control, and software engineering best ...

$195 - $260/hr

Advanced Analytics & Modeling: Design, develop, and validate predictive models, statistical ... Experience with DevSecOps practices, CI/CD pipelines, and version control (e.g., Git) for ...

$85 - $130/hr

... and predictive analytic methods in support of our energy utility clients' customer programs teams ... Describe complex data and modeling concepts in writing and presentation formats to a wide audience ...

$85 - $130/hr

... and predictive analytic methods in support of our energy utility clients' customer programs teams ... Describe complex data and modeling concepts in writing and presentation formats to a wide audience ...

$85 - $110/hr

Experience applying AI/ML tools such as OCR, NLP, or predictive modeling to automation use cases ... Proficiency with version control tools (e.g., Git). * Experience developing APIs or integrating ...

New

Showing results 21-40

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 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 Kentucky?

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

What job categories do people searching Model Predictive Control jobs in Kentucky look for?

The top searched job categories for Model Predictive Control jobs in Kentucky are:

Infographic showing various Model Predictive Control job openings in Kentucky as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution.

$96 - $110/hr

Other

Posted 4 days ago


Job description

AI Engineer
Miami, FL
Hybrid Role
$70 - $80 per hour

ABOUT THE ROLE

Our client, a leading enterprise cruise line, is seeking a Senior AI Engineer to join their growing team in Miami, FL. This role is focused on building and scaling AI-powered recommendation products that drive guest personalization, pricing, and revenue optimisation. As a Senior AI Engineer, you will operate at the intersection of AI/ML and software engineering, leveraging your expertise to turn models and prototypes into robust, scalable production applications. You will play a key role in evolving recommendation‑engine initiatives from early‑stage solutions and MVPs into enterprise‑grade products used across the business. This is an exciting opportunity to collaborate with cross‑functional teams, drive the evolution of AI products, and make a significant impact on the guest experience and business outcomes.

WHAT YOU'LL DO
  • Design, build, and enhance production‑grade AI‑powered recommendation systems
  • Translate AI/ML models and prototypes into scalable, reliable software solutions
  • Develop production‑quality applications and services, primarily using Python
  • Build and operationalise AI/ML solutions within Databricks environments
  • Develop and maintain CI/CD pipelines, deployment processes, and version‑control practices
  • Integrate LLMs, predictive models, business logic, and behavioural data into recommendation workflows
  • Utilise AI‑assisted development tools and coding agents to accelerate engineering and problem solving
  • Collaborate with AI Engineers, Data Scientists, and business stakeholders to translate business objectives into technical solutions
  • Improve system scalability, reliability, maintainability, and performance as AI products mature
  • Independently troubleshoot problems and drive technical solutions from concept through production
WHAT YOU BRING
  • 4-5+ years of relevant software, AI/ML, or data engineering experience with demonstrated senior‑level engineering maturity
  • Strong Python development skills and experience writing production‑quality code
  • Hands‑on experience building and operationalising AI/ML solutions in production
  • Experience with Databricks and modern data/AI environments
  • Strong understanding of software engineering fundamentals, including CI/CD, automated deployment pipelines, Git/source control, testing, modular design, and production monitoring
  • Experience integrating machine learning models into applications, services, or production workflows
  • Ability to independently solve ambiguous technical problems and align solutions with business objectives
  • Strong written and verbal communication skills
  • Experience building recommendation engines, personalisation platforms, or propensity models (preferred)
  • Experience combining LLMs with traditional machine learning and business‑rule systems (preferred)
  • Understanding of Data Science workflows and common ML modelling approaches (preferred)
  • Experience scaling prototypes or MVPs into enterprise‑grade applications (preferred)
  • Experience with cloud‑based AI architectures and APIs/services for production ML applications (preferred)
  • Familiarity with coding agents and AI‑assisted development tools (preferred)
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