Optimization Analyst
- Remote () •
- |1 year of exp
- |Full Time
Onsite or remote
Not Available
About the job
The Role
As an Optimization Analyst at Axolotis.ai, you will spend most of your time at the modeling table — translating real energy systems into the mathematical formulations our optimization engine solves. You’ll work closely with customers to understand their operations, encode their objectives and constraints, and validate that what we ship reflects their world.
What You’ll Do
Build and maintain optimization models of energy systems — generation, storage, dispatch, fuel flow.
Translate customer operations, data, and constraints into rigorous mathematical formulations.
Work directly with customers to understand their systems and iterate on solutions.
Implement and test model components in Python.
Contribute to documentation, tooling, and customer-facing analysis as we scale.
What We’re Looking For
BS, MS, or Ph.D. in Operations Research, Electrical / Mechanical / Industrial Engineering, Applied Math, or a related quantitative field. MS or Ph.D. preferred.
Strong knowledge of nonlinear optimization is a must, along with working knowledge of LP and MILP — through coursework, thesis, or project experience.
Programming skills in Python; comfortable with object-oriented programming.
Strong written and verbal communication — you’ll explain models to non-mathematicians and ask good questions of domain experts.
Familiarity with modern software development practices (version control, testing, code review).
Nice to Have
Background or coursework in energy / power systems, fuels, or grid operations.
Experience with optimization solvers.
Work Authorization
In compliance with federal law, all persons hired will be required to verify identity and eligibility to work in the United States and to complete the required employment eligibility verification form upon hire. As a seed-stage company we are not currently able to sponsor applicants for work visas.
Why Now
You’d be one of our earliest hires, with the scope and influence that comes with being here this early. Compensation is competitive cash plus meaningful early-stage equity. Our preference is hybrid out of Durham, NC, but remote is possible too for the right candidate.
About the company
