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Model Predictive Control Jobs in Lawrence, MA (NOW HIRING)

TRUE Property Insurance

Sr. Data Scientist

Boston, MA · On-site +1

Lead end-to-end predictive modeling initiatives supporting areas such as pricing and rating ... Experience with version control systems, preferably Git. * Experience with cloud-based data science ...

Jobtailor

Principal Data Scientist

Acton, MA · On-site

... control, sensitivity analysis, and uncertainty quantification * Define causal inference approaches ... Define standards for predictive and machine learning model design, validation, explainability ...

Manulife

AI Engineer - Hybrid

Boston, MA · Hybrid

Operationalize traditional ML models and predictive analytics solutions, including classification ... testing, version control, and cloud-native infrastructure. * Monitor production models for ...

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All JobsModel Predictive Control JobsModel Predictive Control Jobs in Lawrence, MA

Model Predictive Control information

See Lawrence, MA salary details

$57.7K

$101.3K

$137.4K

How much do model predictive control jobs pay per year?

As of Sep 13, 2026, the average yearly pay for model predictive control in Lawrence, MA is $101,319.00, according to ZipRecruiter salary data. Most workers in this role earn between $87,600.00 and $113,300.00 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 job categories do people searching Model Predictive Control jobs in Lawrence, MA look for?

The top searched job categories for Model Predictive Control jobs in Lawrence, MA are:

What cities near Lawrence, MA are hiring for Model Predictive Control jobs?

Cities near Lawrence, MA with the most Model Predictive Control job openings:

Model Predictive Control jobs near you

Senior Motion Planning Engineer - Trajectory Generation

Boston, MA • On-site, Remote

Motional
Motor Vehicle Manufacturing • 501 - 1,000 employees
Learn more about Motionalexternal

$172K - $229K/yr

Full-time

Medical, Dental, Vision, Life, Retirement

Re-posted 14 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.
The salary range for this role is an estimate based on a wide range of compensation factors including but not limited to specific skills, experience and expertise, role location, certifications, licenses, and business needs. The estimated compensation range listed in this job posting reflects base salary only. This role may include additional forms of compensation such as a bonus or company equity. The recruiter assigned to this role can share more information about the specific compensation and benefit details associated with this role during the hiring process.
Candidates for certain positions are eligible to participate in Motional's benefits program. Motional's benefits include but are not limited to medical, dental, vision, 401k with a company match, health saving accounts, life insurance, pet insurance, and more.
Salary Range
$172,000-$229,000 USD
Motional is a driverless technology company making autonomous vehicles a safe, reliable, and accessible reality. We're driven by something more.
Our journey is always people first.
We aren't just developing driverless cars; we're creating safer roadways, more equitable transportation options, and making our communities better places to live, work, and connect. Our team is made up of engineers, researchers, innovators, dreamers and doers, who are creating a technology with the potential to transform the way we move.
Higher purpose, greater impact.
We're creating first-of-its-kind technology that will transform transportation. To do so successfully, we must design for everyone in our cities and on our roads. We believe in building a great place to work through a progressive, global culture that is diverse, inclusive, and ensures people feel valued at every level of the organization. Diversity helps us to see the world differently; it's not only good for our business, it's the right thing to do.
Scale up, not starting up.
Our team is behind some of the industry's largest leaps forward, including the first fully-autonomous cross-country drive in the U.S, the launch of the world's first robotaxi pilot, and operation of the world's longest-standing public robotaxi fleet. We're driven to scale; we're moving towards commercialization of our technology, and we need team members who are ready to embrace change and challenges.
Formed as a joint venture between Hyundai Motor Group and Aptiv, Motional is fundamentally changing how people move through their lives. Headquartered in Boston, Motional has operations in the U.S and Asia. For more information, visit www.Motional.com and follow us on Twitter, LinkedIn, Instagram and YouTube.
Motional AD Inc. is an EOE. We celebrate diversity and are committed to creating an inclusive environment for all employees. To comply with Federal Law, we participate in E-Verify. All newly-hired employees are queried through this electronic system established by the DHS and the SSA to verify their identity and employment eligibility.

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