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Modeling Optimization Engineer Jobs (NOW HIRING)

ANAUTICS INC

Optimization Engineer

Oklahoma City, OK · On-site

Build optimization models for scheduling, allocation, routing, supply chain, and resource planning ... What we're looking for * 4+ years of optimization, operations research, industrial engineering, or ...

Intersect

Optimization Engineer

$217K - $237K/yr

The Optimization Engineer will provide technical leadership in the creation of a programmatic optimization platform that transforms real-time data, forecasting models, and asset intelligence into ...

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How much do modeling optimization engineer jobs pay per hour?

As of Sep 11, 2026, the average hourly pay for modeling optimization engineer in the United States is $53.63, according to ZipRecruiter salary data. Most workers in this role earn between $43.27 and $62.26 per hour, depending on experience, location, and employer.

What is a modeling optimization engineer?

Modeling Optimization Engineers are professionals who use mathematical models, simulations, and optimization techniques to improve systems, processes, or products. They analyze data, develop algorithms, and run simulations to find the most efficient solutions to engineering challenges. These engineers often work in industries such as manufacturing, logistics, energy, and technology, helping organizations save time, reduce costs, and increase performance. Their work involves collaborating with other engineers, using specialized software, and applying advanced mathematics to real-world problems.

What are the key skills and qualifications needed to thrive as a modeling optimization engineer?

To thrive as a Modeling Optimization Engineer, you need a solid background in mathematics, data analysis, and optimization theory, typically supported by a degree in engineering, mathematics, computer science, or a related field. Proficiency with programming languages such as Python or MATLAB, optimization libraries, and modeling software like GAMS or CPLEX is essential. Strong problem-solving abilities, attention to detail, and effective communication make someone stand out in this position. These skills are crucial for developing efficient models and solutions that improve processes and drive decision-making in technical and business environments.

What are some common challenges faced by modeling optimization engineers when collaborating with cross-functional teams?

Modeling Optimization Engineers often work closely with data scientists, software developers, and business stakeholders to implement and refine optimization models. One common challenge is translating complex mathematical concepts into practical solutions that align with business objectives, which requires strong communication and collaboration skills. Additionally, integrating optimized models into existing systems can be difficult due to varying technical standards or data quality issues. Being adaptable and proactive in addressing feedback from different team members is essential for ensuring successful project outcomes.

What are popular job titles related to Modeling Optimization Engineer jobs?

For Modeling Optimization Engineer jobs, the most frequently searched job titles are:

Infographic showing various Modeling Optimization Engineer job openings in the United States as of September 2026, with employment types broken down into 93% Full Time, and 7% Contract. Highlights an 80% In-person, 3% Hybrid, and 17% Remote job distribution, with an average salary of $111,552 per year, or $53.6 per hour.

Systems Modeling & Optimization Engineer

Mountain View, CA • Hybrid

Waymo
Internet and IT • 1 - 5K employees
Learn more about Waymoexternal

Full-time

Re-posted 13 days ago

Job description

Hardware Engineering is an innovative and collaborative group of electrical, mechanical, reliability, software and vehicle engineers. We design, build, and perfect the products which are the eyes and ears of Waymo's autonomous driving technology, and integrate those products into vehicle platforms. We're seeking curious and talented teammates to keep us moving in the right direction.

This role follows a hybrid work schedule and you will report to a Systems Engineer.

You will:

  • Build unified modeling and simulation tools for vehicle energy consumption and fleet-level Total Cost of Ownership (TCO).
  • Develop physics-based simulation models of energy consumption across all vehicle operating modes and environmental conditions.
  • Develop a city-level fleet simulator to evaluate interactions across operations models, fleet orchestration, vehicle platform architecture and infrastructure.
  • Use these simulation tools to inform critical vehicle/system architecture decisions.
  • Collaborate with SW, Product, Data Science and Operations teams, using these models to inform production fleet orchestration software and operations/infrastructure roadmaps.

You have:

  • 5+ years of work experience in systems modeling and data science.
  • Experience using Python/Matlab/similar programming language to build physics-based models and simulations.
  • Experience in data analytics and data-based modeling.
  • Strong fundamental education/training in Mechanical Engineering, Electrical Engineering, Physics or a related engineering field.
  • Experience leading and delivering cross-functional workstreams/projects.
  • Experience communicating complex technical analyses effectively.

We prefer:

  • Experience with applying machine learning models in real world applications
  • Experience using agentic coding tools like Claude Code, Codex, Antigravity etc.
  • Experience in physics-based modeling/simulation of electric vehicle powertrains or other electrical + mechanical + thermal domains.
  • Experience applying Operations Research or other optimization approaches to real-world problems.

Apply