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Model Predictive Control Jobs in Oregon (NOW HIRING)

... and predictive analytics. Build scalable machine learning and deep learning models using image ... control, and operational efficiency. As a senior technical contributor, you will drive end-to-end ...

AI Solutions Engineering Delivery Lead

Portland, OR · On-site

$108K - $143K/yr

You will work on developing predictive models, conducting statistical analysis, and creating data ... control and continuous improvement of AI solutions, closely collaborating with business ...

... predictive modeling. * -Foster growth and utility of Cost of Quality within the company through ... Control (SPC), Gage R&R, Pareto Charts etc. using tools like JMP, Minitab. Our commitment We ...

Senior Business Intelligence Engineer

OR · On-site +1

$51 - $66.25/hr

Strong pattern recognition and predictive modeling skills. Preferred qualifications * Knowledge of Python, Scala, and open-source data tools. * Proficiency with version control tools such as Git ...

... control. Architect and refine our bad debt and credit memo approval frameworks to refine for ... Demonstrated experience building automated variance models or predictive analytics for deal ...

Analyze quantum device performance data and develop predictive models for device optimization ... Cryogenic control of qubits * Electrical measurements of spin qubits, singlet-triplet qubits ...

Principal Software Engineer, AI

OR · On-site +1

$134K - $180K/yr

By combining our scale, insights, and AI innovation, we're building the industry's first Predictive ... Design and own the access control and RBAC model for the context layer - a genuinely hard problem ...

... models, sub-metering, budgeting, variances as directed by Management and/or Leadership. • Conduct ... and predictive maintenance program for task scheduling, routines, and performance. Program to ...

Showing results 41-58

Model Predictive Control information

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 are popular job titles related to Model Predictive Control jobs in Oregon?

For Model Predictive Control jobs in Oregon, the most frequently searched job titles are:

What job categories do people searching Model Predictive Control jobs in Oregon look for?

The top searched job categories for Model Predictive Control jobs in Oregon are:

What cities in Oregon are hiring for Model Predictive Control jobs?

Cities in Oregon with the most Model Predictive Control job openings:

Infographic showing various Model Predictive Control job openings in Oregon as of September 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution.

Vision Systems Engineer 4

Tualatin, OR • On-site

Lam Research Corporation
Manufacturing • 10K+ employees

Full-time

Re-posted 3 days ago


Lam Research rating

8.2

Company rating: 8.2 out of 10

Based on 46 frontline employees who took The Breakroom Quiz


Job description

The group you'll be a part of
In the Global Products Group, we are dedicated to excellence in the design and engineering of Lam's etch and deposition products. We drive innovation to ensure our cutting-edge solutions are helping to solve the biggest challenges in the semiconductor industry.
The impact you'll make
At Lam, as a Product Engineer, you thrive in high-stakes, dynamic environment, driving product development at the forefront of the semiconductor equipment industry. Collaborating closely with customers and internal teams, you will provide real-time problem-solving to customer challenges and to enhance our products. Your passion for engaging with customers and innovative engineering drives progress in our industry, tackling the once unsolvable.
In this role, you will directly contribute to Equipment Intelligence team in The Deposition Group.
What you'll do
  • Design, develop, and deploy computer vision algorithms for detection, classification, segmentation, anomaly detection, and predictive analytics.
  • Build scalable machine learning and deep learning models using image, video, and multimodal sensor data.
  • Lead the complete data science lifecycle, including data collection, labeling, feature engineering, model training, validation, deployment, and monitoring.
  • Develop robust image-processing pipelines utilizing modern computer vision frameworks and cloud technologies.
  • Define data quality standards and establish model performance metrics to ensure production readiness.
  • Collaborate with process engineers, software developers, hardware engineers, and product teams to deliver integrated vision solutions.
  • Conduct root-cause analysis and use advanced analytics to improve yield, process stability, and equipment performance.
  • Drive innovation by evaluating emerging AI, machine learning, and computer vision technologies.
  • Mentor junior engineers and provide technical guidance on best practices in data science and machine learning.

Who we're looking for
We are seeking a highly skilled Vision System Data Science Engineer to lead the design, development, and deployment of advanced computer vision and machine learning solutions for complex industrial and manufacturing applications. The ideal candidate combines deep expertise in data science, computer vision, machine learning, and software engineering to transform image and sensor data into actionable insights that improve product quality, process control, and operational efficiency. As a senior technical contributor, you will drive end-to-end vision system development, collaborate with cross-functional teams, and provide technical leadership in AI-driven imaging and analytics initiatives.
Minimum Qualifications:
Master's degree in Data Science, Computer Science, Physics, or related field with 8+ years of relevant experience; or Ph.D. with 5+ years of experience.
Strong expertise in:
Computer Vision
Machine Learning and Deep Learning
Statistical Modeling and Experimental Design
Image Processing and Pattern Recognition
Proficiency C/C++ , in Python and scientific computing libraries such as:
TensorFlow and/or PyTorch
OpenCV
Experience developing and deploying production AI/ML systems.
Strong knowledge of CNNs, object detection, segmentation, and anomaly detection methodologies.
Experience with cloud platforms (Azure, AWS, or GCP) and MLOps practices.
Ability to handle large-scale structured and unstructured datasets.
Preferred qualifications
  • Experience in semiconductor manufacturing, industrial automation, robotics, medical imaging, or advanced inspection systems.
  • Knowledge of optical systems, cameras, sensors, and imaging hardware.
  • Experience with edge AI deployment and real-time inference systems.
  • Familiarity with SQL, Spark, Databricks, and distributed computing environments.
  • Increased process efficiency, yield, or product quality through AI-driven insights.
  • Successful deployment and adoption of vision solutions in production environments.
  • Technical leadership and influence across multiple engineering programs.

Our commitment
We believe it is important for every person to feel valued, included, and empowered to achieve their full potential. By bringing unique individuals and viewpoints together, we achieve extraordinary results.
Lam Research ("Lam" or the "Company") is an equal opportunity employer. Lam is committed to and reaffirms support of equal opportunity in employment and non-discrimination in employment policies, practices and procedures on the basis of race, religious creed, color, national origin, ancestry, physical disability, mental disability, medical condition, genetic information, marital status, sex (including pregnancy, childbirth and related medical conditions), gender, gender identity, gender expression, age, sexual orientation, or military and veteran status or any other category protected by applicable federal, state, or local laws. It is the Company's intention to comply with all applicable laws and regulations. Company policy prohibits unlawful discrimination against applicants or employees.
Lam offers a variety of work location models based on the needs of each role. Our hybrid roles combine the benefits of on-site collaboration with colleagues and the flexibility to work remotely and fall into two categories - On-site Flex and Virtual Flex. 'On-site Flex' you'll work 3+ days per week on-site at a Lam or customer/supplier location, with the opportunity to work remotely for the balance of the week. 'Virtual Flex' you'll work 1-2 days per week on-site at a Lam or customer/supplier location, and remotely the rest of the time.
Our Perks and Benefits
At Lam, our people make amazing things possible. That's why we invest in you throughout the phases of your life with a comprehensive set of outstanding benefits.

What Lam Research employees say

Pay

Benefits

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About Lam Research

Sourced by ZipRecruiter

Lam Research designs and builds products for semiconductor manufacturing, including equipment for thin film deposition, plasma etch, photoresist strip, and wafer cleaning processes.

Industry

Manufacturing

Company size

10,000+ Employees

Headquarters location

Fremont, CA, US

Year founded

1980

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