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About the Role

We are seeking an experienced R&D Engineer III to join our EPE Research and Development team. This role combines expertise in power systems engineering with advanced computational research — including machine learning, adaptive control, and simulation-based modeling — to develop next-generation models that support grid planning, control, and reliability. The primary responsibility is to design, develop, and validate research-driven solutions and modeling frameworks that address emerging challenges in modern power systems, including data center interconnection and large-scale system stability. You will work closely with power system engineers, software developers, and research scientists to translate cutting-edge research into practical, deployable models and tools.

Responsibilities

Design, develop, and validate advanced modeling techniques, including machine learning-based surrogate models, digital twins, and stability certification methods, to support power systems planning and control applications.
Utilize Python and other relevant languages to automate research workflows, build adaptive control tools, advanced generator/load models, and streamline power system simulations and analysis.
Communicate research findings and technical model capabilities through internal presentations, technical reports, and peer-reviewed publications.
Support technical demonstrations for internal teams and clients.
Collaborate with power system engineers, software developers, and cross-functional research teams to integrate novel modeling approaches into EPE's engineering and software offerings.
Serve as a technical resource for translating research capabilities into tailored solutions for client engagements and internal product development.
Test, validate, and troubleshoot research software and models to ensure accuracy, reliability, and performance in real-world power system contexts.

Requirements

Ph.D. or Master's degree in Electrical Engineering with a focus on power systems, controls, or applied machine learning; a Ph.D. is strongly preferred.
Demonstrated research experience in power systems stability analysis, control systems, or machine learning applications in energy systems.
Deep understanding of power systems fundamentals, including transmission and distribution planning, grid dynamics, and stability analysis.
Strong programming skills in Python.
Experience using deep learning frameworks (e.g., PyTorch, TensorFlow) and scientific computing libraries.
Strong presentation and technical writing skills.
Familiarity with software development and testing practices.
Excellent problem-solving skills, particularly in diagnosing and resolving issues in simulation-based or data-driven power system models.
Proficiency in power system simulation software such as PSS/E, PSCAD, PSLF, Aspen, or TARA.
Experience conducting power system studies such as Steady State, Short Circuit, or Dynamic and Transient Stability analysis.
Experience with model predictive control (MPC), meta-learning, or in-context learning methods applied to dynamical or physical systems.
Experience developing digital twins or surrogate models for grid-connected assets.
Familiarity with cloud-based software development and integration of power system models.
Knowledge of AI-driven or large language model (LLM)-based applications in power systems.
Track record of peer-reviewed publications and/or peer review service for IEEE or related technical venues.
Experience mentoring junior researchers, interns, or students.

Skills

Power systems engineering
Machine learning
Adaptive control
Simulation-based modeling
Python
PyTorch
TensorFlow
Deep learning frameworks
Scientific computing libraries
Presentation skills
Technical writing skills
Software development practices
Testing practices
Problem-solving
PSS/E
PSCAD
PSLF
Aspen
TARA
Steady State analysis
Short Circuit analysis
Dynamic and Transient Stability analysis
Model predictive control (MPC)
Meta-learning
In-context learning
Digital twins
Surrogate models
Cloud-based software development
AI-driven applications
Large language model (LLM)-based applications

Location

City, State

Work Type

Occasional travel may be needed (10% or less)

Experience Level

R&D Engineer III
Experienced

Education Level

Ph.D. or Master's degree in Electrical Engineering with a focus on power systems, controls, or applied machine learning
Ph.D. strongly preferred

Benefits

Comprehensive health and wellness benefits including medical, dental, and vision with 100% premium coverage for you
Generous PTO and paid holidays
MyShare Employee Ownership Program
Work with industry leaders
401K, up to a 4% match (100% vested from day 1)

About the Company

Be a part of an innovative team shaping the grid of the future through advanced energy intelligence.
For more than half a century, Electric Power Engineers (EPE) has partnered with power and energy clients across the globe, providing consulting expertise and energy intelligence software solutions for complex engineering and grid modeling challenges.
As leaders in the renewables space, we are focused on building a modern, secure, and resilient grid.
Join us in making an impact on the communities we serve and the environment in which we live.
Together we can transform the future of energy.

Equal Opportunity

EPE is an equal opportunity/AA/Disability/Veteran employer.
The EEO is the Law poster, and its supplement are available using the following links: EEOC is the Law Poster