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Combinatorial Optimization Jobs in Oregon (NOW HIRING)

Combinatorial Optimization information

See Oregon salary details

$43.9K

$150.6K

$212.5K

How much do combinatorial optimization jobs pay per year?

As of Jul 31, 2026, the average yearly pay for combinatorial optimization in Oregon is $150,621.00, according to ZipRecruiter salary data. Most workers in this role earn between $125,300.00 and $176,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Combinatorial Optimization Specialist, and why are they important?

To thrive as a Combinatorial Optimization Specialist, you need a solid background in mathematics, computer science, and operations research, often supported by an advanced degree in a related field. Familiarity with programming languages (such as Python, C++, or Java), optimization libraries, and mathematical modeling tools like CPLEX or Gurobi is typically required. Strong analytical thinking, problem-solving skills, and effective communication help you devise and explain complex solutions to stakeholders. These skills are crucial for developing efficient algorithms and models that address challenging optimization problems in various industries.

How does a Combinatorial Optimization specialist typically collaborate with other departments within an organization?

Combinatorial Optimization specialists frequently work cross-functionally, partnering with data scientists, software engineers, and business analysts to translate complex business problems into mathematical models. They help teams identify optimal solutions for scheduling, routing, resource allocation, and other operational challenges. Effective communication is crucial, as specialists must explain complex algorithms to non-technical stakeholders and integrate their solutions into broader business processes. Collaborative teamwork and iterative problem-solving are common in this role.

What is the difference between Combinatorial Optimization vs Data Analyst?

AspectCombinatorial OptimizationData Analyst
Required CredentialsMathematics, Operations Research, Computer Science degreesStatistics, Data Science, Business Analytics degrees
Work EnvironmentResearch labs, consulting firms, tech companiesCorporate offices, finance, marketing departments
Industry UsageLogistics, manufacturing, AI, supply chainFinance, marketing, healthcare, retail

While both roles involve analytical skills, Combinatorial Optimization focuses on solving complex mathematical problems to find optimal solutions, often in logistics and operations. Data Analysts interpret data to inform business decisions, working across various industries. Understanding these differences helps clarify career paths and employer expectations.

What is combinatorial optimization?

Combinatorial optimization is a field in mathematics and computer science focused on finding the best solution from a finite set of possible solutions. It involves problems where you need to arrange, select, or group discrete objects according to certain rules to achieve an optimal outcome. Examples include scheduling, routing, and assignment problems. Techniques such as linear programming, branch and bound, and heuristics are often used to solve these problems. Combinatorial optimization is widely applied in logistics, operations research, computer science, and engineering.
What are popular job titles related to Combinatorial Optimization jobs in Oregon? For Combinatorial Optimization jobs in Oregon, the most frequently searched job titles are:
What job categories do people searching Combinatorial Optimization jobs in Oregon look for? The top searched job categories for Combinatorial Optimization jobs in Oregon are:
What cities in Oregon are hiring for Combinatorial Optimization jobs? Cities in Oregon with the most Combinatorial Optimization job openings:
Infographic showing various Combinatorial Optimization job openings in Oregon as of July 2026, with employment types broken down into 2% As Needed, 18% Full Time, 5% Part Time, 7% Temporary, 64% Contract, and 4% Nights. Highlights an 24% Physical, 1% Hybrid, and 75% Remote job distribution, with an average salary of $150,621 per year, or $72.4 per hour.

Senior Machine Learning Engineer, Operations Research

Instacart

OR • Remote

$204K/yr

Other

Re-posted 22 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:

We are looking for a Senior Machine Learning Engineer with a strong Operations Research background to join the Service Availability & Routing team within Instacart's Logistics organization. In this role, you will work at the intersection of combinatorial optimization, mathematical programming, and AI to solve high-impact problems in the fulfillment space - including order batching, shopper routing, service availability prediction, and real-time assignment. You'll partner closely with engineering, product, and data science to ship models and algorithms that directly influence Instacart's profitability and shopper experience at scale.

The Logistics & ML group is responsible for the intelligence and execution behind Instacart's fulfillment system. The team optimizes a multi-sided marketplace to ensure customers get their orders on-time and in high quality, shoppers get efficient and fulfilling work, and retailers and consumer brands get reasonable business. The team tackles hard problems in a variety of spaces, such as matching, pricing, and geospatial, as well as foundational problems executing on a high throughput system with dynamic data.

About the Job:

  • Design, develop, and deploy machine learning solutions to tackle practical challenges in the marketplace.
  • Collaborate closely with product managers, data scientists, and backend engineers to deeply understand business needs and create impactful ML applications.
  • Actively engage with diverse stakeholders to ensure that solutions are well-integrated and aligned with business goals.
  • Push the envelope on our operational efficiency by continually refining and advancing our algorithms and models.


About You:

Minimum Qualifications:

  • 3+ years of industry experience using machine learning to solve real-world problems with large datasets
  • Have strong programming skills in Python and fluency in data manipulation (SQL, Pandas) and Machine Learning (scikit-learn, XGBoost, Keras/Tensorflow) tools
  • Have strong analytical skills and problem-solving ability
  • Are a strong communicator who can collaborate with diverse stakeholders across all levels
  • Graduate degree (masters or PhD) in Operations Research or Industrial Engineering or closely related field

Preferred Qualifications:

  • Knowledge of deep learning frameworks and methodologies
  • Experience in applying machine learning and optimization techniques to solve marketplace problems


#LI-Remote


What Instacart employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


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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