ZipRecruiter

Log In

1

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

STR

Lead Software Engineer

Woburn, MA · On-site +1

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 ...

STR

Lead Software Engineer

Woburn, MA · On-site

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 ...

STR

Lead System Engineer

Woburn, MA · On-site +1

$157K - $224K/yr

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 ...

Apply Early

STR

Lead System Engineer with Security Clearance

Woburn, MA · On-site

$157K - $224K/yr

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 ...

STR

Lead System Engineer

Woburn, MA · On-site

$157K - $224K/yr

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 ...

STR

Lead Software Engineer

Woburn, MA · On-site +1

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 ...

Apply Early

FortifyIQ

Data & AI Engineer (Remote)

Salem, MA · Remote

$125K - $150K/yr

Understanding of statistical modeling and predictive maintenance. * Experience with cloud environments (AWS, Azure, GCP) and version control (Git). * Knowledge of MLOps principles (deployment ...

next page

Showing results 1-20

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

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 Jul 7, 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 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.
What are popular job titles related to Model Predictive Control jobs in Boston, MA? For Model Predictive Control jobs in Boston, MA, the most frequently searched job titles are:
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:
Model Predictive Control jobs near you
Infographic showing various Model Predictive Control job openings in Boston, MA as of July 2026, with employment types broken down into 96% Full Time, and 4% Contract. Highlights an 100% In-person job distribution, with an average salary of $104,918 per year, or $50.4 per hour.

Research Scientist I/II, AI for Process Engineering

Lila Sciences

Cambridge, MA • On-site

$176K - $304K/yr

Full-time

Medical, Dental, Vision, Life

Posted 14 days ago

Job description

Your Impact at LILA
As a member of our team in the Physical Sciences division, you will design and build intelligent agent-driven systems that enable AI-accelerated and AI-orchestrated process engineering across a broad range of industrial applications. The core mission of this role is to develop methods by which AI agents can reason about, design, simulate, optimize, and operate complex physical and chemical processes using existing or ML-driven process engineering tools. You will focus on creating agentic infrastructures that allow AI systems to plan and execute multi-step process engineering workflows, ranging from process synthesis and flowsheet generation to steady-state and dynamic simulation, control strategy design, and techno-economic evaluation. Your work will directly shape how Lila's scientific superintelligence performs closed-loop autonomous process engineering to solve real-world problems.
What You'll Be Building
  • Architect and implement agentic frameworks that support end-to-end process engineering workflows, including process setup, simulation, optimization, and analysis.
  • Develop AI agents capable of autonomously planning, executing, and iterating on process engineering tasks using existing tools (e.g., steady-state and dynamic simulators, optimizers, and data systems).
  • Explore agentic approaches for advanced tasks such as process intensification, control co-design, real-time optimization, and closed-loop learning from operational data.
  • Improve robustness, interpretability, and reproducibility of agent-driven process engineering workflows; build internal tooling for debugging, observability, validation, and auditability.
  • Work with interdisciplinary teams to apply agentic process engineering to a broad range of industrial applications

What You'll Need to Succeed
  • PhD or equivalent experience in Chemical Engineering, Industrial Engineering, Systems Engineering, or a closely related field.
  • Research experience in method development for process engineering, a strong publication record in this area or established industry experience
  • Hands-on experience with process simulation and optimization tools (commercial or open-source), including steady-state and dynamic modeling.
  • Proficiency in Python and scientific/engineering computing ecosystems
  • Experience integrating external engineering tools or simulators into automated workflows via APIs, scripting interfaces, or custom wrappers.
  • Familiarity with distributed systems, HPC environments, cloud platforms, or scalable compute infrastructure.

Bonus Points For
  • Experience developing or integrating agentic frameworks, autonomous planners, or multi-step tool-using AI systems for engineering or scientific domains.
  • Experience building computational pipelines, automation systems, or tool-use frameworks for complex engineering or scientific workflows.
  • Experience with digital twins, real-time optimization, or model-predictive control frameworks.
  • Background in techno-economic analysis (TEA), life-cycle assessment (LCA), or sustainability-driven process design.
  • Contributions to open-source engineering software, ML infrastructure, workflow engines, or agent frameworks.

Compensation
We offer competitive base compensation with bonus potential and generous early-stage equity. Your final offer will reflect your background, expertise, and expected impact.
U.S. Benefits. Full-time U.S. employees receive a comprehensive benefits program including medical, dental, and vision coverage; employer-paid life and disability insurance; flexible time off with generous company wide holidays; paid parental leave; an educational assistance program; commuter benefits, including bike share memberships for office based employees; and a company subsidized lunch program.
International Benefits. Full-time employees outside the U.S. receive a comprehensive benefits program tailored to their region. USD salary ranges apply only to U.S.-based positions; international salaries are set to local market.
Expected Base Salary Range
$176,000-$304,000 USD
About LILA
Lila Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges. We believe science is the most inspiring frontier for AI. Rather than hard-coding expert knowledge into tools, LILA builds systems that can learn for themselves.
LILA combines advanced AI models with proprietary AI Science Factory™ instruments into an operating system for science that executes the entire scientific method autonomously, accelerating discovery at unprecedented speed, scale, and impact across medicine, materials, and energy. Learn more at www.lila.ai.
Guided by our core values of truth, trust, curiosity, grit, and velocity, we move with startup speed while tackling problems of historic importance. If this sounds like an environment you'd love to work in, even if you don't meet every qualification listed above, we encourage you to apply.
We're All In
Lila Sciences is committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.
Information you provide during your application process will be handled in accordance with our Candidate Privacy Policy.
A Note to Agencies
Lila Sciences does not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to Lila Sciences or its employees is strictly prohibited unless contacted directly by Lila Science's internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of Lila Sciences, and Lila Sciences will not owe any referral or other fees with respect thereto.

Apply