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Model Predictive Control Jobs in Denver, CO (NOW HIRING)

Mid Computer Scientist

Aurora, CO · On-site

$69K - $158K/yr

Experience with version control tools, including git, GitLab, GitHub, or Bitbucket * Knowledge of statistical analysis, predictive modeling, and machine learning met hods * Ability to design and ...

Experience with version control tools, including git, GitLab, GitHub, or Bitbucket * Knowledge of statistical analysis, predictive modeling, and machine learning methods * Ability to design and ...

Computer Scientist, Mid

Aurora, CO · On-site

$69 - $158/hr

Experience with version control tools, including git, GitLab, GitHub, or Bitbucket * Knowledge of statistical analysis, predictive modeling, and machine learning met hods * Ability to design and ...

Computer Scientist, Mid

Aurora, CO · On-site

$69K - $158K/yr

Experiencewith version control tools, including Git, GitLab, GitHub, or Bitbucket * Knowledge ofstatistical analysis, predictive modeling, and MLmethods * Ability todesign anddevelopautomated ...

Mid Computer Scientist

Aurora, CO · On-site

$69K - $158K/yr

Experience with version control tools, including Git, GitLab, GitHub, or Bitbucket * Knowledge of statistical analysis, predictive modeling, and ML met hods * Ability to design and develop automated ...

Make (and Keep) more money, so they control their own destiny. About the Role The Senior or Staff ... Design, implement, and deploy advanced predictive models, algorithms, and experiments that drive ...

Make (and Keep) more money, so they control their own destiny. About the Role The Senior or Staff ... Design, implement, and deploy advanced predictive models, algorithms, and experiments that drive ...

Showing results 21-40

Model Predictive Control information

See Denver, CO salary details

$56.6K

$99.4K

$134.8K

How much do model predictive control jobs pay per year?

As of Aug 22, 2026, the average yearly pay for model predictive control in Denver, CO is $99,401.00, according to ZipRecruiter salary data. Most workers in this role earn between $85,900.00 and $111,200.00 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 Denver, CO?

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

What job categories do people searching Model Predictive Control jobs in Denver, CO look for?

The top searched job categories for Model Predictive Control jobs in Denver, CO are:

What cities near Denver, CO are hiring for Model Predictive Control jobs?

Cities near Denver, CO with the most Model Predictive Control job openings:

Infographic showing various Model Predictive Control job openings in Denver, CO 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 $99,401 per year, or $47.8 per hour.

Applied AI Scientist

MAXAR TECHNOLOGIES, INC.

Westminster, CO • On-site

$128 - $187/hr

Other

Retirement

Posted 2 days ago

New


Job description

Vantor is forging the new frontier of spatial intelligence, helping decision makers and operators navigate what’s happening now and shape what’s coming next. Vantor is a place for problem solvers, changemakers, and go-getters—where people are working together to help our customers see the world differently, and in doing so, be seen differently. Come be part of a mission, not just a job, where you can: Shape your own future, build the next big thing, and change the world.To be eligible for this position, you must be a U.S. Person, defined as a U.S. citizen, permanent resident, Asylee, or Refugee.Export Control/ITAR: Certain roles may be subject to U.S. export control laws, requiring U.S. person status as defined by 8 U.S.C. 1324b(a)(3).Please review the job details below.ResponsibilitiesDesign, develop, and deploy AI-driven applications that transform large-scale geospatial data into actionable insights and predictive intelligence.Build and operate end-to-end AI/ML pipelines including data ingestion, preprocessing, feature engineering, training, evaluation, and production inference.Productionize reasoning models, vision-language models (VLMs), and multimodal AI systems that combine imagery, geospatial signals, and structured data.Architect enterprise-grade training and experimentation frameworks, including automated pipelines, experiment tracking, benchmarking, and reproducible evaluation.Create synthetic datasets and test harnesses to validate model performance, robustness, and edge-case behavior in real-world operational environments.Work closely with domain experts, software engineers, product managers, and research partners to translate complex Earth intelligence challenges into deployable AI solutions.Optimize models and inference systems for scalability, latency, cost efficiency, and reliability on modern cloud infrastructure.Implement and maintain production inference systems, including monitoring, model versioning, retraining workflows, and performance tracking.Stay current with the latest advances in foundation models, generative AI, multimodal learning, and reasoning systems, and translate research breakthroughs into practical systems.Maintain high engineering standards through code reviews, documentation, experimentation discipline, and collaborative problem solving.Help shape the next generation of Earth AI capabilities through collaboration with leading research organizations and technology partners.Minimum QualificationsMS or PhD in Computer Science, Machine Learning, Artificial Intelligence, Applied Mathematics, or a related technical field, or equivalent practical experience.5+ years of experience building and deploying machine learning systems in production environments.Demonstrated experience designing and delivering end-to-end ML pipelines, including data processing, training automation, evaluation frameworks, and scalable inference.Hands-on experience developing and deploying deep learning models, particularly in one or more of the following areas:Vision-language models (VLMs)Multimodal learningReasoning modelsLarge language models (LLMs)Computer vision or geospatial AIStrong programming skills in Python, with experience using modern ML frameworks such as PyTorch, TensorFlow, or JAX.Experience building reproducible experimentation pipelines, including model evaluation, dataset versioning, and experiment tracking.Experience deploying models into production environments using modern cloud infrastructure and containerized systems.Familiarity with distributed training, large-scale data processing, and model optimization techniques.Ability to collaborate across research, engineering, and product teams to bring advanced AI capabilities into real-world applications.Preferred QualificationsExperience working with geospatial data, remote sensing, satellite imagery, or Earth observation systems.Experience building or fine-tuning foundation models, multimodal models, or agentic AI systems.Familiarity with Google Cloud Platform (GCP), including large-scale AI/ML infrastructure.Experience implementing model monitoring, evaluation pipelines, and automated retraining systems.Contributions to open-source AI projects, research publications, or patents.Pay Transparency: To support pay transparency, Vantor includes salary ranges in all U.S. job postings. Starting pay for this role will fall within the listed range and will be based on factors such as experience, qualifications, skills, location, and market conditions. Candidates who meet the minimum requirements for the role should not expect to receive compensation at the top of the range. The listed range reflects the expected pay for this position, and final offers will be determined based on each candidate’s experience, expertise, and alignment with the role. The base pay for this position within Colorado is: $128,000.00 - $170,000.00 - $187,000.00 annually. The base pay for this position within New Jersey is: $128,000.00 - $170,000.00 - $187,000.00 annually. The base pay for this position within Delaware is: $128,000.00 - $170,000.00 - $187,000.00 annually. The base pay for this position within the Washington, DC metropolitan area is: $140,000.00 - $187,000.00 - $205,700.00 annually. The base pay for this position within California is: $147,000.00 - $196,000.00 - $215,600.00 annually.For all other states, we use geographic cost of labor as an input to develop market-driven ranges for our roles, and as such, each location where we hire may have a different range.Benefits: Vantor offers a competitive total rewards package that goes beyond the standard, including a robust 401(k) with company match, mental health resources, and unique perks like student loan repayment assistance, adoption reimbursement and pet insurance to support all aspects of your life. You can find more information on our benefits at: https://www.Vantor.com/careersAdditionally, this position is incentive eligible with a target based on contribution, company performance, and/or individual results achieved; the specific incentive plan and target amount will be determined based on the role and breadth of contributions.The application window is three days from the date the job is posted and will remain posted until a qualified candidate has been identified for hire. If the job is reposted regardless of reason, it will remain posted three days from the date the job is reposted and will remain reposted until a qualified candidate has been identified for hire.The date of posting can be found on Vantor's Career page at the top of each job posting.To apply, submit your application via Vantor's Career page.EEO Policy: Vantor is an equal opportunity employer committed to an inclusive workplace. We believe in fostering an environment where all team members feel respected, valued, and encouraged to share their ideas. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, sex, gender identity, sexual orientation, disability, protected veteran status, age, or any other characteristic protected by law. #J-18808-Ljbffr

Maxar Technologies logo

About Maxar Technologies

Sourced by ZipRecruiter

Maxar Technologies, headquartered in Denver, CO, US, is a space technology company established in 1969. Operating in the Aerospace Industry, Maxar's key areas of business include Earth Intelligence and Space Infrastructure. The products they offer are critical for global communications, environmental monitoring, national security, intelligence operations, disaster response, and more. Passionate about unlocking the potential of space, Maxar's mission is "to build a better world by harnessing space technology". The company prides itself on advancing state-of-the-art technology, delivering exceptional customer service, and driving growth.

Industry

Space research administration

Company size

1,001 - 5,000 Employees

Headquarters location

Denver, CO, US

Year founded

1969