Power Systems Optimization Engineer

Electric Power Engineers • Austin, TX

4d • Remote

About The Position

Electric Power Engineers (EPE) is seeking a Power Systems Optimization Engineer to join its software team. The position combines transmission planning expertise with mathematical optimization to identify least-cost, technically sufficient mitigation portfolios and quantify their economic value. The engineer will design, prototype, and productionize optimization methods for large, nonlinear, mixed-integer grid-planning problems, and collaborate with planners, developers, and product owners to integrate dependable tools into EPE’s planning platform. The position is remote, with occasional travel of 10% or less.

The work includes selecting combinations of network upgrades, storage, reconfiguration, and operational measures to address violations across multiple scenarios and contingencies; developing economic analysis and cost-allocation methods; and creating scalable optimization formulations and algorithms. The engineer will prototype in Python, validate results against full AC power-flow results from industry tools, and work with developers to deploy methods as robust services. The role also involves benchmarking and sensitivity analysis, incorporating real-world planning constraints, communicating results to engineers, clients, and stakeholders, supporting onboarding and tailored deployments, and documenting methodologies and validation.

Requirements

• Master’s degree or PhD in Electrical Engineering, Operations Research, Applied Mathematics, or a related field, focused on power systems and/or optimization; a bachelor’s degree with equivalent experience will be considered.
• At least 3 years of experience applying optimization to power systems problems, such as transmission expansion planning, optimal power flow, unit commitment, or resource or portfolio planning, in industry or research.
• Strong foundation in linear, mixed-integer, and nonlinear optimization, convex relaxations, and decomposition methods.
• Proficiency in Python and at least one optimization modeling framework, such as Pyomo, JuMP, CVXPY, PuLP, or gurobipy, and commercial or open-source solvers such as Gurobi, CPLEX, Xpress, HiGHS, or Ipopt.
• Understanding of power flow, contingency analysis, and transmission planning, including the U.S. transmission system and ISO/RTO structures.
• Strong communication skills, including the ability to explain complex models, assumptions, and results to engineers and non-technical audiences.
• Problem-solving skills, especially for diagnosing infeasibility, numerical issues, and scaling challenges in large models.

Nice To Haves

• Hands-on transmission planning or interconnection study experience in steady-state, short-circuit, or dynamic stability studies using tools such as PSS/E, PSLF, PowerWorld, TSAT, or TARA.
• Experience with transmission expansion planning, network upgrade cost allocation, or interconnection cluster studies such as SPP DISIS, MISO DPP, or PJM cycle studies.
• Experience with production-cost or capacity-expansion models such as PLEXOS, PROMOD, GridView, Aurora, or PowerSIMM, and economic planning metrics such as APC, adjusted production cost, or benefit-cost ratios.
• Experience with stochastic or robust optimization and scenario-based planning under uncertainty.
• Familiarity with power systems optimization packages such as PowerModels.jl, pandapower, PyPSA, or MATPOWER.
• Software engineering experience with Git, testing (pytest), code review, and deploying models in cloud or distributed environments.
• Knowledge of machine-learning methods used to accelerate optimization, such as surrogate models, warm-starting, or constraint screening.
• Publications or open-source contributions in power systems optimization.

Responsibilities

• Formulate and solve mitigation portfolio optimization problems to select least-cost combinations of transmission upgrades, storage, reconfiguration, and other measures that address thermal, voltage, and stability violations across cases, seasons, and contingencies.
• Develop methods for cost allocation, benefit-cost and production-cost-informed evaluation, and comparison of alternative portfolios for planning and interconnection decisions.
• Develop MILP/MINLP formulations, power-flow relaxations and linearizations, decomposition approaches, and heuristics that scale to large systems.
• Prototype optimization methods in Python, validate them against full AC power-flow results from industry tools, and collaborate with developers to deploy them as robust, scalable services.
• Verify optimized portfolios by resimulating them and quantify optimality gaps, runtime, and sensitivity to assumptions.
• Work with transmission planners to capture constraints such as lead times, outage feasibility, cost estimates, and planning criteria in model constraints and objectives.
• Explain optimization results, trade-offs, and assumptions to engineers, clients, and stakeholders; support onboarding and tailored deployments.
• Write methodology papers, model formulations, and validation reports.

Benefits

• Medical, dental, and vision benefits with 100% premium coverage for the employee.
• Generous PTO and paid holidays.
• MyShare Employee Ownership Program.
• 401(k) with up to a 4% match, 100% vested from day one.
• Opportunity to work with industry leaders.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level