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Model Predictive Control Jobs in Alberta (NOW HIRING)

Architect, implement, and tune advanced control strategies, such as Model Predictive Control (MPC), for pipeline systems * Discrete Logic: Design state machines for operational mode management ...

... predictive modelling, collaborating with clients and internal teams to produce actionable ... Develop mineral prospectivity models, geological classification models, and geoscience data ...

... predictive models, metrics, and dashboards that deliver actionable insights * Visualize and report ... Understanding of version control systems (e.g., Git) for collaborative development * Ability to ...

... predictive models, metrics, and dashboards that deliver actionable insights * Visualize and report ... Understanding of version control systems (e.g., Git) for collaborative development * Ability to ...

... predictive insights and scalable growth. What you'll work on: * Own the multi-year vision and ... control improvement across the portfolio. * Establish SLAs, intake triage, and support models ...

IT ERP Sustainment Specialist

Calgary, AB ยท Hybrid

CA$115K - CA$145K/yr

Identify and deliver automation and AI-driven enhancements (e.g., RPA, predictive analytics) to ... Enbridge's FlexWork (hybrid work model) offers eligible employees (Manager and below) the option to ...

IT ERP Sustainment Specialist

Edmonton, AB ยท Hybrid

CA$115K - CA$145K/yr

Identify and deliver automation and AI-driven enhancements (e.g., RPA, predictive analytics) to ... Enbridge's FlexWork (hybrid work model) offers eligible employees (Manager and below) the option to ...

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 job categories do people searching Model Predictive Control jobs in Alberta look for? The top searched job categories for Model Predictive Control jobs in Alberta are:
Infographic showing various Model Predictive Control job openings in Alberta as of July 2026, with employment types broken down into 1% As Needed, 73% Full Time, 21% Part Time, 1% Temporary, 3% Contract, and 1% Nights. Highlights an 95% Physical, 1% Hybrid, and 4% Remote job distribution.

Advanced Process Control Engineer

CruxOCM

Calgary, AB โ€ข On-site

Full-time

Re-posted 23 days ago


Job description

About CruxOCM

CruxOCM is the leading automation company in heavy industry, specifically targeting the energy sector. We are a venture capital-backed company dedicated to transforming this industry.

Control room operators require the most effective tools to perform their jobs safely and efficiently, while minimizing environmental impact and maximizing revenue. Considering that pilots have autopilot software, it's time for control room operators to have a comparable solution.

About the Role

We are looking for an Advanced Process Control Engineer who will be a technical authority on control automation. You will be responsible for leading the development and integration of advanced control algorithms with Crux software, industrial systems and workflows.ย 

The Advanced Process Control Engineer, reporting to the Advanced Process Control Engineer Lead, is a key role that blends leadership skills, personal skills, and technical expertise. You will join a team focused on delivering automation solutions to improve pipeline operations within control room environments. This role involves close collaboration with customer teams (Control operation, SCADA engineering) and internal teams (Deployment, Product, and Engineering) to ensure alignment on customer requirements and project delivery.

Job Responsibilities
  • Advanced Control: Architect, implement, and tune advanced control strategies, such as Model Predictive Control (MPC), for pipeline systemsย 

  • Discrete Logic: Design state machines for operational mode management, construct fail-safe conditions and safety checks, and protective interlocks

  • Control System Testing: Outline and execute test plans to validate controller performance and safety requirements, perform root cause analyses (RCAs), and troubleshoot errors or undesired behaviours in simulation-based and production environmentsย 

  • Algorithm Design: Create and help maintain tools for data analysis, system identification, empirical and physics-based model tuning

  • System Integration: Enable rapid integration and deployment of Crux products, by developing playbooks, standardizing processes and leveraging the latest engineering tools.

  • Quality Assurance: Ensure all deliverables meet the high safety and reliability standards required for heavy industry environments.

  • Relationship Building: Develop deep, trust-based relationships with client-side operators and technical leads.

  • Internal Synergy: Align cross-functional teams to ensure a unified delivery approach.

Requirements
  • Bachelor's degree in Chemical, Electrical, or Mechanical engineering or related field (post-graduate studies focusing on advanced control systems or MPC preferred)

  • Hold a Professional Engineer (P.Eng.) designation or be eligible to obtain licensure in Canada

  • Experience with control system design, controller tuning, execution of simulation-based testing, data processing and analysis, system integration

  • Familiarity with the process of system identification to develop empirical models of input-output relationships

  • Experience with writing specification documents, technical reports

  • Proficiency with Python and version control software (e.g. GitHub)

Prior experience or knowledge of the following is considered an asset:

  • A reasonable understanding of hydraulic theory, fluid dynamics, numerical methods, optimization algorithms/dynamic programming

  • Experience with OPC communication protocols and/or SCADA systems

  • Experience with DNV Synergi Pipeline Simulator (SPS) or Atmos Simulation Suite for performing transient pipeline simulations

What We Offer
  • Competitive compensation package, including equity

  • Comprehensive health benefits

  • Remote-first work environment

  • Flexible work arrangements

  • Professional development opportunities

  • Growth-mindset culture

  • A diverse and inclusive environment

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