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Model Predictive Control Jobs in Pennsylvania (NOW HIRING)

Vitro Flat Glass

Sr. R&D Engineer

Cheswick, PA

$95K - $123K/yr

Deep understanding of process control methodologies such as feedback, feedforward, model predictive control, inferential control, etc. * Excellent understanding of optimization methods such as LP, QP ...

Vitro Architectural Glass

Sr. R&D Engineer

Cheswick, PA · On-site

$95K - $131K/yr

Deep understanding of process control methodologies such as feedback, feedforward, model predictive control, inferential control, etc. * Excellent understanding of optimization methods such as LP, QP ...

Waabi

Research Engineer, World Models

Pittsburgh, PA · On-site +1

$155K - $269K/yr

Model distillation - Collaborate closely with Research Scientists to translate cutting-edge model ... You have built and deployed generative or predictive models of the physical world, focusing on ...

Waabi

Research Engineer, World Models

Pittsburgh, PA · On-site +1

$155K - $269K/yr

Model distillation - Collaborate closely with Research Scientists to translate cutting-edge model ... You have built and deployed generative or predictive models of the physical world, focusing on ...

Waabi

Research Scientist, World Models

Pittsburgh, PA · On-site +1

$155K - $269K/yr

Model distillation. - Collaborate with engineers to integrate models into large-scale, distributed ... You have built generative or predictive models of the physical world with scale and efficiency in ...

PPG Industries, Inc.

Modeling Engineer

Allison Park, PA · On-site

... predictive accuracy, and influence product development. You will also apply optimization methods ... S. export control regulations (i.e., U.S. citizen or lawful permanent resident) to comply with ...

PPG

Modeling Engineer

Allison Park, PA · On-site

... predictive accuracy, and influence product development. You will also apply optimization methods ... S. export control regulations (i.e., U.S. citizen or lawful permanent resident) to comply with ...

Munich Re

Data Scientist, AI

Philadelphia, PA · On-site +1

We focus on developing and maintaining predictive models that support all domains across the ... version control, and agile frameworks using tools like Azure DevOps. Skills / Knowledge ...

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All JobsModel Predictive Control JobsModel Predictive Control Jobs in Pennsylvania

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 (MPC) 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 (MPC) 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.
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Model Predictive Control jobs near you
Infographic showing various Model Predictive Control job openings in Pennsylvania 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 96% Physical, 1% Hybrid, and 3% Remote job distribution.
Senior Motion Planning Engineer - Trajectory Generation

Senior Motion Planning Engineer - Trajectory Generation

Motional

Pittsburgh, PA • On-site, Remote

$118K - $156K/yr

Other

Posted 26 days ago

Job description

Mission Summary:
On our Motion team, you will leverage your expertise in motion planning, robotics, and software development to advance the capabilities of production-ready autonomous vehicles. In this role, you will conduct innovative research, lead design processes, and implement performance-critical algorithms that enable safe, comfortable, and intuitive autonomous vehicle behaviors across Motional's fleet of robotaxis.

If you are passionate about autonomous driving, thrive on solving challenging optimization problems, and are eager to make a significant impact in a rapidly evolving field, we want to hear from you.

Technical Scope:
  • Develop state-of-the-art motion control and trajectory optimization algorithms to ensure safe and comfortable vehicle motion 
  • Design and build robust and scalable software that enables real on-road impact by evaluating different control techniques and motion planning algorithms
  • Provides high-quality code and design reviews (C++) based on a deep understanding of the teams' services and technologies
  • Leverage modern development toolchains, including testing, simulation, and continuous integration, to enable rapid development cycles
Role responsibilities:
  • Understands and explains trade-offs, complex concepts to peers and leaders to drive decisions.
  • Collaborate with teams working on (ML) decision/behavior planning, prediction, and vehicle control to build comprehensive and integrated solutions
  • Creates project proposals that drive long-term technical roadmaps and span multiple sub-systems.
  • Mentor junior team members to develop a culture of product-focused engineering, research, and development.
What we're looking for:
  • 3+ years of C++ software development
  • Bachelors, Masters, or PhD degree preferred in Robotics, Computer Science, Computer Engineering, Electrical Engineering, or a related field.
  • Experience with Model Predictive Control (MPC), motion planning, planning under uncertainty, vehicle dynamics and control, and simulation environments
  • Understanding of numerical optimization algorithms (interior point method, sequential quadratic programming, etc)
  • Experience with optimization solvers (IPOPT, Gurobi, etc)
  • Past experience owning and leading technical development on features from problem formulation, algorithm design, through implementation
  • Knowledge of Python is a bonus

We encourage a hybrid schedule with in-office time at one of our locations in Boston or Pittsburgh to support collaboration, or this role can be fully remote.

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