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Model Predictive Control Jobs in Washington (NOW HIRING)

Systems Engineer, Senior

Annapolis Junction, MD ยท On-site

$106K - $146K/yr

Harnessing the most advanced technology and solutions, we strengthen defenses and control ... modeling, predictive analytics, or decision-support systems * Knowledge of data science, machine ...

Harnessing the most advanced technology and solutions, we strengthen defenses and control ... modeling, predictive analytics, or decision-support systems * Knowledge of data science, machine ...

Systems Engineer, Senior

Annapolis Junction, MD ยท On-site

$106K - $146K/yr

Harnessing the most advanced technology and solutions, we strengthen defenses and control ... modeling, predictive analytics, or decision-support systems * Knowledge of data science, machine ...

Modeler III with Security Clearance

Arlington, VA ยท On-site

$63 - $81.75/hr

Applies broad understanding of military command & control and force structure at the unified ... Model (STORM) and/or Advanced Framework for Simulation, Integration, and Modeling (AFSIM) * Eight ...

Export Control/ITAR: Certain roles may be subject to U.S. export control laws, requiring U.S ... models, algorithms, and frameworks to improve objectivity, completeness, and predictive value of ...

CBRN Analyst

Arlington, VA ยท On-site

$101K - $201K/yr

... Control and Communication (NC3) Division. Work will be performed onsite in the Arlington, VA area (Pentagon). Job Responsibilities: * Execute and refine predictive hazard models, data simulations ...

... Control and Communication (NC3) Division. Work will be performed onsite in the Arlington, VA area (Pentagon). Job Responsibilities: * Execute and refine predictive hazard models, data simulations ...

Showing results 41-60

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 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 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 are popular job titles related to Model Predictive Control jobs in Washington? For Model Predictive Control jobs in Washington, the most frequently searched job titles are:
What job categories do people searching Model Predictive Control jobs in Washington look for? The top searched job categories for Model Predictive Control jobs in Washington are:
Infographic showing various Model Predictive Control job openings in Washington as of July 2026, with employment types broken down into 1% As Needed, 74% Full Time, 19% Part Time, 1% Temporary, 4% Contract, and 1% Nights. Highlights an 96% Physical, 1% Hybrid, and 3% Remote job distribution.

Systems Engineer, Senior

Everwatch

Annapolis Junction, MD โ€ข On-site

$106K - $146K/yr

Other

Re-posted 24 days ago


Job description

Job TitleSystems Engineer, SeniorOverview

EverWatch is a government solutions company providing advanced defense, intelligence, and deployed support to our country's most critical missions. ย We are a full-service government solutions company. Harnessing the most advanced technology and solutions, we strengthen defenses and control environments to preserve continuity and ensure mission success.

EverWatch employees are focused on tackling the most difficult challenges of the US Government. We offer the best salaries and benefits packages in our industry - to identify and retain the top talent in support of our critical mission objectives.

Commitment to Non-Discrimination:

All qualified applicants will receive consideration for employment without regard to disability, status as a protected veteran or any other status protected by applicable federal, state, local, or international law.

Responsibilities

Are you looking for an opportunity to combine your technical skills with big picture thinking to make an impact in national security? You understand your customer's environment and how to develop the right systems for their mission. Your ability to translate real-world needs into technical specifications makes you an integral part of delivering a customer focused engineering solution.ย ย 

As a Systems Engineer on our team, you will lead the design, development, and implementation of enterprise-scale data models, ontologies, and distributed systems that support advanced analytics, mission operations, and national security objectives. Your customers will trust you to not only architect and integrate enterprise systems, but also modernize and evolve them using advanced technologies including AWS, Kubernetes, Apache Kafka, and scalable semantic data frameworks. On our team, you'll have the opportunity to broaden your expertise across enterprise systems engineering, ontology and model development, cloud adoption, and high-throughput distributed computing environments. You'll collaborate with cross-functional teams, mentor engineers on modern development practices, and help deliver scalable, resilient, and well-documented mission platforms supporting next-generation intelligence and analytics capabilities.

Join us. The world can't wait.ย 

Qualifications

You Have:ย 

  • Experience with designing and implementing enterprise-scale ontologies, logical data models, graph modeling, semantic technologies, entity resolution, taxonomy management, and metadata tagging to support advanced analytics and discovery
  • Experience with architecting and integrating scalable backend systems and high-throughput data pipelines using Apache Kafka, including cluster management, topic configuration, message-key strategies, topic compaction, and performance tuning
  • Experience with deploying and orchestrating containerized applications within Kubernetes (K8s) environments, including the use of CRDs, Operators, and cloud-native architectures in AWS
  • Experience with Java, Spring Boot, API development, OpenAPI/Swagger documentation, and enterprise-grade backend service implementation
  • Experience with CI/CD automation, Infrastructure as Code (Terraform/CloudFormation), and enterprise systems engineering best practices within distributed computing environments
  • Knowledge of monitoring, observability, and performance management tools and frameworks including Prometheus, Grafana, ELK, Kafka clusters, and graph database technologies
  • Ability to translate business and operational requirements into technical specifications, architectural diagrams, scalable engineering solutions, and long-term platform strategies
  • Ability to provide technical leadership through troubleshooting complex distributed systems issues, mentoring engineering teams, and communicating architectural concepts to technical and executive stakeholders
  • TS/SCI with a polygraph
  • Bachelor's degree in System Engineering, Computer Science, Information Systems, Engineering Science, Engineering Management, or related discipline from an accredited college or university and 20+ years of experience or 25+ years experience in lieu of degree

Nice If You Have:ย 

  • Experience with Neo4j graph databases, including Cypher, APOC, and Graph Data Science (GDS) for advanced graph analytics and modeling
  • Experience with ontology and semantic web standards, including OWL (Ontology Web Language) and RDF (Resource Description Framework), for knowledge representation and linked data systems
  • Experience with social media sentiment analysis and its application to financial modeling, predictive analytics, or decision-support systems
  • Knowledge of data science, machine learning, and graph-based analytics applied to large-scale structured and unstructured datasets
  • Ability to design and apply quantitative, statistical, and computational methods to complex enterprise or mission-driven data problems
  • Ability to integrate and analyze multi-source datasets to develop semantic, scalable, and analytically rich data models

Clearance:

Applicants selected will be subject to a security investigation and may need to meet eligibility requirements for access to classified information; TS/SCI clearance with a polygraph is required.ย 

Compensation at EverWatch is determined by various factors, including but not limited to location, the individual's particular combination of education, knowledge, skills, competencies, and experience, as well as contract-specific affordability and organizational requirements. The projected compensation range for this position is $100.96 to $115.38 per hour.ย  The estimate displayed represents the typical compensation range for this position and is just one component of EverWatch's total compensation package for employees.

Clearance LevelTS/SCI FSPJob LocationsUS-MD-Annapolis JunctionSkillsSystem Engineering, Architecture, Apache, Kafka, Kubernetes, Java, springboot, APIMinMaxEmployment Type: OTHER