Power Systems Optimization Engineer

Electric Power Engineers • Austin, TX

3d • Remote

About The Position

Electric Power Engineers (EPE) is seeking a Power Systems Optimization Engineer to join its software team. The role combines transmission planning expertise with mathematical optimization to develop methods for selecting least-cost, technically sufficient mitigation portfolios and quantifying their economic value. The engineer will design, prototype, validate, and productionize optimization approaches for large, nonlinear, and mixed-integer grid-planning problems, working with planners, software developers, and product owners to incorporate them into EPE’s planning platform.

The position focuses on mitigation portfolio optimization, economic analysis, nonlinear and mixed-integer modeling, algorithm development, validation, and benchmarking. The engineer will translate real-world planning constraints into model objectives and constraints, verify optimized portfolios through resimulation, and communicate results and assumptions to engineers, clients, and other stakeholders. The position is remote, with occasional travel of 10% or less.

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 mathematical optimization, including linear, mixed-integer, and nonlinear programming, 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.
• Solid understanding of power flow, contingency analysis, and transmission planning concepts, including the US 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.
• Excellent problem-solving skills, particularly in diagnosing infeasibility, numerical issues, and scaling challenges in large models.

Nice To Haves

• Hands-on transmission planning or interconnection study experience, including 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 practices, including Git, testing with 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 optimization problems selecting least-cost combinations of transmission upgrades, storage, reconfiguration, and other mitigations to resolve thermal, voltage, and stability violations across cases, seasons, and contingencies.
• Build methods for cost allocation, benefit-cost and production-cost-informed evaluation, and comparison of alternative portfolios.
• Develop MILP/MINLP formulations, AC/DC power-flow relaxations and linearizations, decomposition approaches, and heuristics that scale to large real-world systems.
• Prototype optimization methods in Python, validate them against full AC power-flow results from industry tools, and work with developers to deploy robust, scalable services.
• Verify optimized portfolios by resimulating them and quantify optimality gaps, runtime, and sensitivity to assumptions.
• Partner with transmission planners to capture constraints such as lead times, outage feasibility, cost estimates, and planning criteria, and translate them into 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

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

What This Job Offers

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