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Model Predictive Control Jobs in Oregon (NOW HIRING)

Waabi

Research Scientist, World Models

OR · On-site +1

$155K - $269K/yr

Model distillation. - Collaborate with engineers to integrate models into large-scale, distributed ... You have built generative or predictive models of the physical world with scale and efficiency in ...

Intel

FFEO FORGE Statistician

Hillsboro, OR · On-site

You will design and apply statistical methodologies, develop predictive models, and create ... process control systems. - Knowledge of machine learning frameworks and model training ...

New

A-dec, Inc.

AI Engineer, Sr

Newberg, OR

$109K - $150K/yr

The AI Engineer, Sr will design, build, and deploy AI powered systems including predictive models ... Understanding of software engineering best practices including version control, testing, and ...

A-dec, Inc.

AI Engineer, Sr

Newberg, OR · On-site

$109K - $150K/yr

The AI Engineer, Sr will design, build, and deploy AI powered systems including predictive models ... Understanding of software engineering best practices including version control, testing, and ...

Roseburg

Sawfiling Coordinator

Dillard, OR · On-site

Oversee department inventory and inventory control including tools and shop equipment * Prepare ... Model company core values Required Qualifications * 3+ years' predictive/preventative maintenance ...

SupportFinity™

AI Engineer, Sr

Newberg, OR · On-site

$140 - $220/hr

The AI Engineer, Sr will design, build, and deploy AI powered systems including predictive models ... Understanding of software engineering best practices including version control, testing, and ...

with Stimson Lumber

Plant Manager

Tillamook, OR · On-site

Oversee preventive, predictive, and proactive maintenance programs, including planning, scheduling ... model for safe industrial behavior. * Collaborate with other departments (Finance, HR, Sales ...

A-dec Inc.

AI Engineer, Sr

Newberg, OR · On-site

$109K - $150K/yr

... predictive insights across various business functions. Responsibilities : • Design, develop ... Python for building AI models, automation, and production services • SQL for working with ...

Stimson Lumber Company

Plant Manager

Tillamook, OR · On-site

$165 - $195/hr

Oversee preventive, predictive, and proactive maintenance programs, including planning, scheduling ... model for safe industrial behavior. * Collaborate with other departments (Finance, HR, Sales ...

What the Tech, Bend

Energy Analyst

Portland, OR · On-site

$80 - $100/hr

We uniquely pair traditional energy storage with predictive load control technology to ... Research and model site economics, operating strategies, and enrollment procedures for demand ...

360training

Data Architect Manager

Strong understanding of lakehouse, medallion, data warehouse, and data modeling patterns, including ... control, documentation, and observability. * Experience preparing enterprise data for AI-enabled ...

Instacart

Senior Marketing Decision Scientist II

OR · On-site +1

Build and productionize predictive models (e.g., LTV, churn/propensity, audience response, budget ... version control (Git). * Demonstrated ability to translate ambiguous business questions into ...

U.S. Silica Company

Journey Electrician

Vale, OR · On-site

$45 - $48/hr

... control systems and tools following electrical code, manuals, specifications, schematics, and ... Be a role model and advocate for safety among co-workers * Perform all tasks in an environmentally ...

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All JobsModel Predictive Control JobsModel Predictive Control Jobs in Oregon

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:

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

Senior Applied Scientist II, Ads Optimization

Instacart

OR • On-site, Remote

Full-time

Re-posted 14 days ago

Instacart rating

7.1

Company rating: 7.1 out of 10

Based on 31 frontline employees who took The Breakroom Quiz

28th of 64 rated delivery companies

Job description

Overview

The Advertiser Optimization team is the decision-making engine of Instacart's $1B+ ads business. We own the systems responsible for Bidding, Pacing, Budgeting, and Targeting: converting stated advertiser goals into real-time auction actions. Our mission is to maximize realized Advertiser Value by deciding when to participate, how much to bid, and how fast to spend, all while balancing User Experience and Platform Revenue.

We are hiring a Senior Applied Scientist II to lead the algorithmic direction of these systems. This is a role for someone who thinks in terms of control theory, constrained optimization, and auction economics, and who can translate those frameworks into production code that makes millions of decisions per day. You will formulate problems from first principles, shape the technical roadmap, and own systems end-to-end from mathematical design through production deployment through impact measurement.

About the Job
  • Design and evolve real-time bid optimization systems that translate advertiser goals (target ROAS, budget constraints) into optimal auction bids under uncertainty. Formulate the bidding problem as constrained optimization and build the feedback mechanisms that keep bids aligned with realized outcomes.
  • Build intelligent budget pacing algorithms that distribute spend across time and auction opportunities. The core challenge: allocating a finite daily budget across stochastic demand while maximizing total value, subject to advertiser constraints and time-varying conversion dynamics.
  • Develop the analytical frameworks that connect bidding, pacing, and budgeting into a coherent optimization objective.
  • Shape auction mechanics including reserve pricing, multi-slot allocation, and bid-to-price mapping. Reason about mechanism design tradeoffs between advertiser outcomes, platform revenue, and marketplace efficiency.
  • Own the full research-to-production loop: diagnose system behavior from large-scale data, formulate hypotheses, design experiments, ship production code, and measure impact. Write technical strategy documents that set the algorithmic direction for the team.
About YouMinimum Qualifications
  • Graduate degree (Masters or PhD) in operations research, applied mathematics, control systems, computational economics, or a related quantitative field.
  • 8+ years of experience building and deploying optimization or control systems in production environments (not just research prototypes).
  • Strong foundation in at least two of: feedback control theory (PID, MPC), convex and stochastic optimization, auction theory and mechanism design, dynamic programming.
  • Proficiency in one of the following languages: Go, Java, C++ for production systems and Python for data analysis and offline pipelines.
  • Demonstrated ability to translate mathematical formulations into production code that runs at scale (millions of decisions per day, sub-100ms latency constraints).
Preferred Qualifications
  • Experience with real-time bidding systems, ad auction optimization, or computational advertising at scale.
  • Background in budget-constrained allocation methods. Experience with adaptive control or model-predictive control in production systems.
  • Familiarity with causal inference and experimental design for evaluating algorithmic changes in marketplace settings.
  • Track record of shaping technical strategy and driving cross-functional alignment between engineering, product, and data science.

What Instacart employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

Instacart logo

About Instacart

Sourced by ZipRecruiter

Instacart, based in San Francisco, CA, US, operates within the retail industry, specifically grocery delivery and pick-up service. It is recognized as a pioneer in this field, delivering fresh groceries from local stores directly to customers' doors. The company, which launched its services in 2012, continues to pioneer change in the online grocery shopping sector through its commitment to cutting-edge technology, new business ideas, and dedicated service.

Industry

Technology, communication and media

Company size

10,000+ Employees

Headquarters location

San Francisco, CA, US

Year founded

2012

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