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Model Predictive Control Jobs in Toronto, ON (NOW HIRING)

AI Engineer

Toronto, ON ยท On-site

Develop and deploy models using modern AI/ML frameworks; ensure model performance, monitoring, and ... Knowledge of version control using Jenkins, GitHub Actions, GitLab CI, Jenkins, or Azure DevOps * ...

Develop and deploy models using modern AI/ML frameworks; ensure model performance, monitoring, and ... Knowledge of version control using Jenkins, GitHub Actions, GitLab CI, Jenkins, or Azure DevOps * ...

Laval, QC; Moncton, NB; Montreal, QC; Ottawa, ON; Quebec City, QC; Regina, SK; Saint John, NB ... model design and solution architecture (drivers, assumptions, scenarios, workflows, reporting ...

Permanent Work Model: Hybrid Reference code: 133603 Primary Location: Toronto, ON All Available ... Laval, QC; Moncton, NB; Montreal, QC; Ottawa, ON; Quebec City, QC; Regina, SK; Saint John, NB;

Applied Machine Learning Scientist I

Toronto, ON ยท On-site

CA$105K - CA$125K/yr

Develop, deploy, and maintain Predictive and Generative AI models for use cases such as Agentic AI ... Experience applying software engineering practices such as code reviews, version control, testing ...

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 job categories do people searching Model Predictive Control jobs in Toronto, ON look for?

The top searched job categories for Model Predictive Control jobs in Toronto, ON are:

What cities near Toronto, ON are hiring for Model Predictive Control jobs?

Cities near Toronto, ON with the most Model Predictive Control job openings:

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

Service Transition & Operational Resiliency Leader

BMO Capital Markets

Toronto, ON โ€ข Hybrid

Full-time

Medical, Life, Retirement

Posted 17 days ago


Job description

Application Deadline:

08/30/2026

Address:

4100 Gordon Baker Road

Job Family Group:

Technology

This is an Individual Contributor role and HYBRID (2 days/week in office at 4100 Gorgon Baker Road). Remote is not an option.

About the Role:

As a Service Transition & Operational Resiliency Leader, you will be responsible for driving excellence across the Service Transition function as well as play a pivotal role in ensuring technology and business services are introduced or changed to production with stability, control, and measurable business value. This role will lead the operational and governance pillar of the Service Transition team, complementing the Lead Engineer who focuses on the technical and automation pillar. Together, the Service Transition Lead and the Engineering Lead will create a unified leadership model that connects business strategy, operational performance, and technology enablement. The Service Transition & Resiliency Lead will own Operational Excellence, KPI and metrics governance, and portfolio health oversight - embedding a culture of accountability, data-driven decision-making, and continuous improvement across all transitions and operational processes.

Key Accountabilities:

  • Lead the Operational Excellence program for the Service Transition function, focusing on process standardization, efficiency, and control
  • Strengthen the governance framework of Operational Readiness across projects, E&P service delivery teams, and production support teams, ensuring consistent adherence to enterprise technology standards, practices, and operating models
  • Enhance and manage the KPI and Metrics framework for Service Transition - tracking portfolio health, process efficiency, readiness quality, and post Go-Live performance
  • Lead the creation and delivery of executive-level reporting - providing transparency into Service Transition performance, key risks, and operational trends
  • Drive continuous improvement through metric-based insights; identify bottlenecks, optimize workflows, and prioritize automation opportunities in partnership with the Lead Engineer
  • In partnership with Senior Manager, develop and maintain a multi-year roadmap for Service Transition, embedding automation, predictive data-analytics capabilities, and AI-assisted decision-making opportunities to improve speed and accuracy
  • Partner with senior leaders and cross-functional teams - from Delivery and Engineering to Risk & Compliance, Security, Service Management and other stakeholder groups to ensure cohesive, organization-side alignment throughout the service lifecycle.
  • Provide leadership to the Service Transition team to foster a culture of accountability, performance, and innovation
  • Represent the Service Transition domain in boarder technical forums, steering committees, and enterprise governance bulletins
  • Broader work or accountabilities may be assigned as needed

Qualifications & Skills

  • Bachelor Degree in Engineering
  • Ideally Certified ITIL/ITSM
  • 8+ years of experience in Service Transition, Operational Readiness, or IT Service Management (ITSM) within a large enterprise or financial institution
  • Strong understanding of ITIL framework (v5 preferred), particularly Service Transition and Service Operations domains
  • Strategic understanding of cloud ecosystems (AWS, Azure) and how cloud architecture, resiliency patterns, and service models influence operational readiness and service transition
  • Demonstrated ability to define multi-year operational strategies, maturity roadmaps, or transformation programs
  • Experience with technology resiliency practices, including disaster recovery planning, failover testing, business continuity integration, or operational risk management
  • Experience using data to drive decision-making, identify bottlenecks, and influence improvement strategies for the team
  • Experience leading organizational change initiatives or implementing new operational models across multiple teams or areas
  • Proven ability to influence senior leaders, drive alignment across diverse stakeholder groups, and navigate complex enterprise structures
  • Demonstrated success leading cross-functional teams through complex service launches, technology changes, or operational transitions
  • Experience with process automation, workflow tools, or Power Platform
  • Exposure to AI-driven process optimization, AI tool integration (Copilot)
  • Excellent communication, influencing, and stakeholder management skills - comfortable working across all levels of the organization

Salary:

Pay Type:

Salaried

The above represents BMO Financial Group's pay range and type.

Salaries will vary based on factors such as location, skills, experience, education, and qualifications for the role, and may include a commission structure. Salaries for part-time roles will be pro-rated based on number of hours regularly worked. For commission roles, the salary listed above represents BMO Financial Group's expected target for the first year in this position.

BMO Financial Group's total compensation package will vary based on the pay type of the position and may include performance-based incentives, discretionary bonuses, as well as other perks and rewards. BMO also offers health insurance, tuition reimbursement, accident and life insurance, and retirement savings plans. To view more details of our benefits, please visit:https://jobs.bmo.com/global/en/Total-Rewards

About Us

At BMO we are driven by a shared Purpose: Boldly Grow the Good in business and life. It calls on us to create lasting, positive change for our customers, our communities and our people. By working together, innovating and pushing boundaries, we transform lives and businesses, and power economic growth around the world.

As a member of the BMO team you are valued, respected and heard, and you have more ways to grow and make an impact. We strive to help you make an impact from day one - for yourself and our customers. We'll support you with the tools and resources you need to reach new milestones, as you help our customers reach theirs. From in-depth training and coaching, to manager support and network-building opportunities, we'll help you gain valuable experience, and broaden your skillset.

To find out more visit us at https://jobs.bmo.com/ca/en.

BMO is committed to an inclusive, equitable and accessible workplace. By learning from each other's differences, we gain strength through our people and our perspectives. Accommodations are available on request for candidates taking part in all aspects of the selection process. To request accommodation, please contact your recruiter.

Note to Recruiters: BMO does not accept unsolicited resumes from any source other than directly from a candidate. Any unsolicited resumes sent to BMO, directly or indirectly, will be considered BMO property. BMO will not pay a fee for any placement resulting from the receipt of an unsolicited resume. A recruiting agency must first have a valid, written and fully executed agency agreement contract for service to submit resumes.