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

Senior AI Engineer

Boston, MA · On-site

$113K - $155K/yr

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

AI/ML Engineer

Boston, MA · On-site

$35 - $45/hr

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

... control (GNC); trajectory optimization; and/or the development of predictive models for vehicle dynamics and weapon system effectiveness (e.g., 6-DoF simulation, intercept analysis). • Solid ...

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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 Jun 9, 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 (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 cities near Lawrence, MA are hiring for Model Predictive Control jobs? Cities near Lawrence, MA with the most Model Predictive Control job openings:
Lead AI Engineer - Semiconductor AI Innovation

Lead AI Engineer - Semiconductor AI Innovation

Onto

Wilmington, MA • On-site

$112K - $147K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 4 days ago


Job description

Onto Innovation is a leader in process control, combining global scale with an expanded portfolio of leading-edge technologies that include: 3D metrology spanning the chip from nanometer-scale transistors to micron-level die-interconnects; macro defect inspection of wafers and packages; metal interconnect composition; factory analytics; and lithography for advanced semiconductor packaging. Our breadth of offerings across the entire semiconductor value chain helps our customers solve their most difficult yield, device performance, quality, and reliability issues. Onto Innovation strives to optimize customers' critical path of progress by making them smarter, faster and more efficient.

Job Summary & Responsibilities

Lead AI Engineer - Semiconductor AI Innovation

Driving AI-Powered Solutions for Semiconductor Equipment Operations

Location: Wilmington, MA (On-site)
Team: AI & Advanced Analytics
Reports to: Senior Director, Engineering
Direct Reports: Will hire and lead a team of 3 AI/ML engineers

About Us

Onto Innovation is a worldwide leader in the design, development, manufacture and support of defect inspection, advanced packaging lithography, process control metrology, and data analysis systems and software used by semiconductor device manufacturers worldwide. Onto Innovation provides a full-fab solution through its families of proprietary products that provide critical yield-enhancing information and real time process control responses, enabling microelectronic device manufacturers to drive down the costs and time to market of their products. The Company's expanding portfolio of equipment and software solutions is used in both the wafer processing and final manufacturing of ICs, and in adjacent markets such as FPD, and LED manufacturing.

We design and manufacture advanced semiconductor inspection and metrology tools. Our solutions power innovation for the world's leading chipmakers. As the industry moves faster than ever, we believe AI will be a key enabler of smarter, faster, and more reliable decision-making in semiconductor manufacturing.

We're building a new AI Innovation Team to explore, develop, and deploy cutting-edge machine learning systems across our product and process ecosystem. You'll be our founding Lead AI Engineer, responsible for setting the vision, building the team, and delivering impactful AI solutions at scale.

About the Role

This is a hands-on technical leadership role. You will work closely with senior tool designers, process engineers, and applications teams to understand complex workflows and data flows. You'll architect, prototype, and productionize AI solutions that accelerate innovation, improve yields, and reduce tool downtime. You will also grow and mentor a team of three engineers specializing in LLMs, computer vision, predictive modeling, and MLOps.

Responsibilities
  • Define the AI strategy and architecture for integrating machine learning into core engineering and manufacturing processes.
  • Partner with tool, process, and applications engineers to map as-is processes and define a to-be AI/automation architecture and deliver measurable outcomes.
  • Ship agentic assistants for use-cases. Stand up LLM + RAG + tool integrations (via MCP servers) that help engineers accelerate tool operation/setup/maintenance and explain trade-offs, grounded in internal docs, logs, and historical inspection outcomes.
  • Lead projects across diverse areas:
    • Predictive maintenance for tool health monitoring and failure detection.
    • Computer vision for wafer defect detection, segmentation, and classification.
    • LLM-based engineering assistants using RAG and MCP agents to make internal knowledge more accessible.
    • Process optimization & yield improvement through data-driven insights and parameter tuning.
    • Simulation and digital twins to model process behaviors and accelerate R&D.
  • Build retrieval-augmented AI assistants to query internal knowledge bases, tools, and logs.
  • Architect robust pipelines for data ingestion, labeling, storage, and retrieval across massive multi-modal datasets (images, telemetry, recipes, logs).
  • Stand up scalable MLOps infrastructure: model registries, monitoring, evaluation, deployment, and governance.
  • Hire, mentor, and manage a team of 3 engineers focused on LLM/Agents, CV/ML, and MLOps/Data.
  • Work cross-functionally to integrate AI solutions into production environments safely and securely.
Minimum Qualifications
  • 5+ years applied ML/AI experience, with 3+ years in a technical leadership role.
  • Hands-on expertise with at least two of the following domains:
    • Large Language Models - RAG, fine-tuning, agent frameworks, prompt optimization.
    • Predictive Modeling - tool failure prediction, anomaly detection, time-series analysis.
    • Computer Vision - defect detection, segmentation, or SEM/optical imaging.
  • Strong background in ML systems architecture and production deployment.
  • Advanced Python proficiency: C++/CUDA familiarity is a plus.
  • Experience with MLOps stacks: containers, CI/CD, Ray Serve/Triton, model registries (e.g., MLflow), and GPU optimization.
  • Strong stakeholder collaboration skills and the ability to translate between engineering, operations, and leadership.
  • Demonstrated success delivering AI-powered products into production.
Nice-to-Haves
  • Familiarity with semiconductor manufacturing, inspection, or metrology.
  • Understanding of fab interfaces and data connectivity (SECS/GEM, GEM300).
  • Prior experience deploying digital twins or simulation-driven optimization.
  • Knowledge of vector databases, retrieval pipelines, and hybrid search.
  • Experience implementing safety, security, and IP protections for AI systems.
  • Exposure to datasets or tools from KLA, ASML, Applied Materials, Onto, Nova, or similar inspection/metrology vendors.
What Success Looks Like
  • 90 days: Map high-value AI opportunities, propose architecture, and deliver a prioritized roadmap.
  • 6 months: Deliver first production pilot (e.g., predictive tool health, RAG assistant, or wafer defect CV model) and hire first two engineers.
  • 12 months: Multiple AI-powered systems integrated into engineering workflows, delivering measurable impact on yield, efficiency, and downtime.
Our Tech Stack
  • LLMs & Agents: OpenAI, Anthropic, HuggingFace, MCP-based connectors, LangChain, LlamaIndex
  • Predictive Models: PyTorch, TensorFlow, Scikit-learn, XGBoost, Time-series ML
  • Computer Vision: PyTorch, OpenCV, Kornia, segmentation/detection architectures
  • Data & Serving: Triton, Ray Serve, MLflow, Kubernetes, Kafka, vector DBs, GPU compute clusters
Why Join Us
  • Build foundational AI infrastructure in one of the most data-rich industries in the world.
  • Lead the team shaping the future of AI-assisted semiconductor engineering.
  • Tackle multi-modal AI challenges at scale-from LLMs to predictive analytics to advanced vision systems.
  • Collaborate with world-class engineers pushing the limits of nanometer-scale inspection and manufacturing.

Qualifications

see above

Onto Innovation Inc. offers competitive salaries and a generous benefits package, including health/dental/vision/life/disability, PTO, 401K plan with employer match, and an Employee Stock Purchase Program (ESPP) along with health & wellness initiatives. We provide a collaborative working environment along with resources, and state-of-the-art tools & equipment to promote success; and a welcoming, inclusive corporate culture where individuals are recognized for their contributions.

Onto Innovation Inc. is an Equal Opportunity Employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, gender, sexual orientation, national origin, genetic information, age, disability, veteran status, or any other legally protected basis.

For positions requiring access to technical data, Onto Innovation Inc., Inc. may have to obtain export licensing approval from the U.S. Department of Commerce - Bureau of Industry and Security and/or the U.S. Department of State - Directorate of Defense Trade Controls. As such, applicants for this position - except US Citizens, US Permanent Residents, and protected individuals as defined by 8 U.S.C. 1324b(a)(3) - may have to go through an export licensing review process.


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About ONTO

Sourced by ZipRecruiter

Industry

Specialized design services

Company size

1 - 10 Employees

Headquarters location

New York, NY, US

Year founded

2021