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Combinatorial Optimization Jobs (NOW HIRING)

We are looking for an AI Optimization Engineer to lead and define our optimization capabilities ... If you are energized by hard combinatorial problems, want to build and own a solver capability from ...

Research Scientist III - AMZ9443129

Seattle, WA · On-site

$159.20K - $215.30K/yr

... combinatorial optimization, integer programming, dynamic programming, network flows and algorithms to design optimal or near optimal solution methodologies to be used by in-house decision support ...

Senior Software Engineer, AI Networking

Seattle, WA

$139.40K - $183.80K/yr

These include tools that use ML-based combinatorial optimization and build space exploration (DSE) techniques. These tools will be employed to optimize AI workloads across large GPU and CPU clusters ...

Senior ML Engineer

$180K - $200K/yr

You'll work across optimization, machine learning, and geometric deep learning on a hard, real-world combinatorial problem. This is a fully distributed team. We expect high autonomy and high ...

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Combinatorial Optimization information

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$41.5K

$142.5K

$201K

How much do combinatorial optimization jobs pay per year?

As of May 31, 2026, the average yearly pay for combinatorial optimization in the United States is $142,460.00, according to ZipRecruiter salary data. Most workers in this role earn between $118,500.00 and $166,500.00 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 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 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.

More about Combinatorial Optimization jobs
What cities are hiring for Combinatorial Optimization jobs? Cities with the most Combinatorial Optimization job openings:
What states have the most Combinatorial Optimization jobs? States with the most job openings for Combinatorial Optimization jobs include:
Infographic showing various Combinatorial Optimization job openings in the United States as of May 2026, with employment types broken down into 89% Full Time, 6% Part Time, and 5% Contract. Highlights an 23% Hybrid, and 77% Remote job distribution, with an average salary of $142,460 per year, or $68.5 per hour.
AI Optimization Engineer

Full-time

Posted 8 days ago


Job description

About Us:
Datacor is the leading provider of software solutions, including ERP, CRM, Asset Tracking, Simulation and Formulation, to the process manufacturing space. We are on a mission to better equip the industry with software solutions and move it forward by building thoughtful, intuitive products that solve our customers' most difficult problems.
We are passionate about serving our customers and helping them use data as a competitive advantage. Our customers make products that extend and sustain lives by sanitizing, fertilizing, beautifying, cleaning, and recycling the world we live in. We at Datacor help our customers make those products you use every day more safely, cost effectively and more efficiently through our technology platforms and applications.
The Role:
At our core, we empower top talent with the autonomy to craft innovative solutions that make a real difference helping our users become better, faster, smarter, and more efficient.
We are looking for an AI Optimization Engineer to lead and define our optimization capabilities across our product suite. Your mission: reinvent how some of the country's leading process manufacturers and distributors manage their end-to-end operations from inbound ingredient arrivals through production sequencing to outbound fleet and delivery optimization.
This is a greenfield role with real depth and full ownership you will set the technical direction, establish the algorithmic foundation, and drive delivery from design through production deployment. You will shape how Datacor approaches optimization across many customers, each operating under their own unique set of business constraints and operational realities. Critically, this role spans multiple Datacor products and cross-functional teams giving you rare visibility and influence across the full business, not just a single product or vertical. You'll lead and collaborate directly with product managers, engineers, and domain experts in a fast-moving team that values your judgment and expertise driving initiatives from problem framing through MVP and into production, seeing your work run in the real world, on the screens of operators making high-stakes decisions every day.
If you are energized by hard combinatorial problems, want to build and own a solver capability from the ground up, and care about delivering things that create real impact this is the role for you.
Responsibilities:
• Define and lead the technical strategy for optimization use cases across Datacor's product portfolio.
• Translate complex, real-world operational constraints into rigorous mathematical models.
• Design, implement, and benchmark optimization algorithms including exact methods, metaheuristics (simulated annealing, tabu search, genetic algorithms), and commercial solvers (OR-Tools, Gurobi, CPLEX, or equivalent).
• Make principled tradeoffs between solution quality, computational cost, and real-time responsiveness.
• Collaborate closely with product, engineering, and design teams to ensure the solver doesn't just work algorithmically it becomes a solution that real users can understand, trust, and act on every day.
• Drive end-to-end delivery of optimization solutions from prototype to production working across cross-functional teams.
• Integrate optimization engines into production software via APIs and enterprise data pipelines.
• Serve as the internal authority on optimization methods communicating algorithm design, performance, and tradeoffs clearly to both technical and business audiences.
• Stay ahead of advances in OR, combinatorial optimization, and applied AI and bring new ideas and thinking that push our capabilities forward.
Qualifications Required:
• Master's degree in Operations Research, Industrial Engineering, Computer Science, Applied Mathematics, or a related quantitative field with 3+ years of hands-on industry experience, or a PhD in a related field.
• Proven track record of taking optimization solutions from problem definition to production with measurable business impact across domains such as supply chain, logistics, production scheduling, vehicle routing, or related fields.
• Proficiency with at least one major OR/optimization framework: Google OR-Tools, Gurobi, CPLEX, HiGHS, SCIP, or equivalent.
• Strong programming skills in Python; C++ or Java a plus.
• Hands-on experience with cloud platforms, particularly AWS, including deploying and scaling computational workloads.
• Familiarity with Large Language Models (LLMs) and generative AI, and an awareness of how they can complement optimization workflows.
• Exceptional communication skills able to translate complex algorithmic concepts into clear, business-relevant terms for non-technical stakeholders, and convey the value of your work in a way that resonates across the organization.
• Ability to model ambiguous, real-world constraints rigorously and defend and advocate for design decisions at all levels of the organization.
• Genuinely curious you ask why the problem exists, not just how to solve it, and you bring that curiosity into every stage of the work.
• Strong product ownership mindset you take responsibility for outcomes, not just outputs, and care about whether your solution actually works for the people using it.
• Outcomes-driven you measure success by the real-world impact your work delivers, not by the sophistication of the technology or elegance of the process behind it. The goal is results that matter to the business and the customer.
Preferred:
• Impactful experience in one or more of the following: transportation, logistics, supply chain, fleet management, manufacturing or mill production scheduling, or the agri-food industry.
• Familiarity with geospatial data and road network routing APIs (e.g., Google Maps Platform, HERE, Mapbox).
• Experience leading optimization work within an Agile, cross-functional product team.
• Comfort integrating optimization outputs into enterprise software workflows and ERP data models.
EOE Statement:
Datacor is an Equal Opportunity Employer and does not discriminate on the basis or race, color, religion, sex, national origin, age, disability, veteran status, or any other protected characteristic.
Use of AI During Interviews:
At Datacor, we value thoughtful problem-solving and authentic perspectives. To ensure a fair and consistent evaluation process, we ask that candidates do not use generative AI tools or outside assistance during live interviews unless explicitly stated otherwise. We're interested in hearing your experience, your approach, and how you think through challenges.