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

Hiarc

Staff Reliability Engineer

Merrimack, NH · On-site

$120 - $180/hr

... thermal control, risk management, supply chain management, performance testing, advanced ... life ‑ modeling), leveraging innovative analytical methods to improve predictive accuracy.

New

Ameriprise Financial

Senior Data Scientist

Boston, MA · On-site

You will create large data sets, provide information-based decision logic and predictive modeling ... control processes for analytics, model development, and validation. * Monitor execution of ...

Winaxis

AI/ML Engineer

Boston, MA · On-site

$32 - $35/hr

... AI, and predictive analytics techniques. Deploy machine learning models into production ... Familiarity with version control systems like Git. Preferred Qualifications Experience with ...

Winaxis

AI/ML Engineer

Boston, MA · On-site

$124K - $149K/yr

... AI, and predictive analytics techniques. Deploy machine learning models into production ... Familiarity with version control systems like Git. Preferred Qualifications Experience with ...

Winaxis

AI/ML Engineer

Boston, MA · On-site

$30 - $35/hr

... AI, and predictive analytics techniques. Deploy machine learning models into production ... Familiarity with version control systems like Git. Preferred Qualifications Experience with ...

Winaxis

AI/ML Engineer

Boston, MA · On-site

$124K - $149K/yr

... AI, and predictive analytics techniques. Deploy machine learning models into production ... Familiarity with version control systems like Git. Preferred Qualifications Experience with ...

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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 Aug 11, 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 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 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

Principal Applied Scientist, Mobile Manipulation Robotics

Amazon

Reading, MA • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 6 days ago

Amazon rating

7.4

Company rating: 7.4 out of 10

Based on 7,079 frontline employees who took The Breakroom Quiz

6th of 39 rated national retailers

Job description

Amazon Robotics is revolutionizing warehouse automation at unprecedented scale. We are looking for a technical lead to own the whole-body planning, control, and optimization stack for the Phoenix mobile manipulation robot. In this role, you will design and ship motion planners and controllers that coordinate all of Phoenix's degrees of freedom (mobile base, torso, arm, and end-effector) as a single unified system, enabling smooth, safe, and production-ready autonomous manipulation in Amazon fulfillment environments.
You will architect whole-body motion planning pipelines (task-and-motion planning, trajectory optimization) that generate collision-free, time-efficient trajectories across the full kinematic chain. You will develop and tune real-time whole-body controllers, including QP-based and model-predictive approaches, and integrate them with the Foundry Controller mainline. A key part of the role is ensuring planner-generated trajectories are high-quality enough to train downstream foundation model policies (e.g., π0.5) at scale. You will also extend Phoenix's Control Barrier Function (CBF) safety architecture, guaranteeing constraint satisfaction from planning through execution.
About the team
Amazon Robotics develops and deploys advanced robotic systems that power Amazon's fulfillment centers worldwide. Our innovations in mobile manipulation, autonomous navigation, and human-robot collaboration are transforming how products move through our network, enabling faster delivery times while creating safer, more ergonomic work environments for our associates.
BASIC QUALIFICATIONS
- PhD in Robotics, Computer Science, Mechanical Engineering, or a related field, with 7+ years of relevant research experience after degree; or Master's degree with 12+ years of equivalent experience
- Experience developing and deploying real-time controllers on physical robotic hardware
- Demonstrated ability to influence technical strategy across multiple teams and organizations
PREFERRED QUALIFICATIONS
- Proficiency in Python and C++ with experience writing production-grade code
- Proven track record of publications at top-tier venues (e.g., CVPR, ICCV, ECCV, NeurIPS, ICRA, RSS, CoRL)
- Experience with real-time perception on resource-constrained hardware (edge compute, embedded GPUs)
- Track record of building perception systems that generalize across multiple sensor configurations or robot platforms
- Experience with foundation models or large-scale self-supervised learning applied to robotics perception
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
USA, MA, North Reading - 198,900.00 - 269,000.00 USD annually

What Amazon employees say

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Benefits

Hours and flexibility

Workplace

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About Amazon

Sourced by ZipRecruiter

Amazon.com, Inc., commonly known as Amazon, is an American multinational technology company. It was founded by Jeff Bezos in 1994 and initially started as an online marketplace for books. Since then, Amazon has expanded its operations and become one of the largest e-commerce companies in the world. Amazon's primary business is its online retail platform, where customers can purchase a vast array of products, including electronics, clothing, books, home goods, and much more. The company offers a convenient and user-friendly shopping experience, with features such as fast shipping, customer reviews, and personalized recommendations. In addition to its e-commerce platform, Amazon has diversified its business into various other areas. One of its notable ventures is Amazon Web Services (AWS), a comprehensive cloud computing platform that provides services such as storage, compute power, and database management to individuals and businesses. AWS has become a leader in the cloud computing industry, powering many websites and applications worldwide. Amazon has also developed its own consumer electronics, including the popular Amazon Kindle e-reader, Fire tablets, Fire TV streaming devices, and the Alexa-powered Echo smart speakers. The Alexa voice assistant, integrated into these devices, allows users to interact with their devices using voice commands, perform tasks, and access information. Furthermore, Amazon has expanded into media and entertainment. It operates Prime Video, a streaming service that offers a wide range of movies, TV shows, and original content. Amazon Music provides a platform for streaming and purchasing digital music, while Audible offers audiobooks and other audio content. The company's commitment to customer satisfaction and convenience is demonstrated by its membership program, Amazon Prime. Prime members receive various benefits, including free two-day shipping, access to streaming services, exclusive deals, and more.

Industry

It services, book publishers, retail, real estate and computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Seattle, WA, US

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