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

By leveraging expertise in machine learning, algorithms, model-predictive control, and software development we build tools that support tactical mission planning and execution, autonomous reasoning ...

Senior Applied Scientist

Reading, MA · On-site

$96K - $131K/yr

... model-predictive control - Experience with imitation learning and reinforcement learning for whole-body control - Experience with simulation environments such as IsaacLab, Mujoco, Drake, etc ...

By leveraging expertise in machine learning, algorithms, model-predictive control, and software development, we build tools that support tactical mission planning and execution, autonomous reasoning ...

By leveraging expertise in machine learning, algorithms, model-predictive control, and software development, we build tools that support tactical mission planning and execution, autonomous reasoning ...

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Model Predictive Control information

See Boston, MA salary details

$59.8K

$104.9K

$142.3K

How much do model predictive control jobs pay per year?

As of Sep 11, 2026, the average yearly pay for model predictive control in Boston, MA is $104,918.00, according to ZipRecruiter salary data. Most workers in this role earn between $90,700.00 and $117,300.00 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 Boston, MA look for?

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

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

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

Infographic showing various Model Predictive Control job openings in Boston, MA as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 22% Part Time, 3% Contract, and 1% Nights. Highlights an 95% Physical, 1% Hybrid, and 4% Remote job distribution, with an average salary of $104,918 per year, or $50.4 per hour.

Senior Robotics Engineer / Navigation

Charlestown, MA • On-site

Motion Recruitment
Recruiting and Staffing Services • 501 - 1,000 employees

$113K - $156K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 11 days ago


Job description

This company is at the forefront of robotics, developing advanced navigation systems for autonomous mobile robots. In this role, you'll have the opportunity to lead and innovate in the field of robotics navigation, optimizing speed and safety for autonomous robot fleets. This is a full time position that is onsite in Boston, MA.
Required Skills & Experience
  • 5+ years of experience in robotics engineering
  • Industry experience developing navigation algorithms for mobile robots
  • Proficient in Python and C++
  • Deep understanding of robot kinematics and dynamics
  • Experience with graph search methods for planning (A*, RRT, PRM)
  • Experience with mathematical optimization techniques (convex optimization, nonlinear programming)
  • Experience with control algorithms for mobile robots (PID, Pure Pursuit, LQR)
  • Experience shipping and supporting navigation features for a fleet of mobile robots
Desired Skills & Experience
  • Experience with trajectory optimization or model-predictive control
  • Experience with collision avoidance and autonomous recovery behaviors
  • Expereince with machine learning techniques for motion planning (behavior cloning, diffusion policies)
  • Experience leading a team of engineers through Scrum process
  • Master's Degree in related field
What You Will Be Doing
Tech Breakdown
  • 20% Python, C++
  • 50% Navigation Algorithms
  • 30% Motion Planning
Daily Responsibilities
  • 75% Hands On
  • 10% Management Duties
  • 15% Team Collaboration

The Offer
You will receive the following benefits:
  • Medical, Dental, and Vision Insurance
  • PTO
  • 401k

Applicants must be currently authorized to work in the US on a full-time basis now and in the future.