Energy Optimization Engineering Intern 🎓

About Redwood Materials

Redwood is localizing a global battery supply chain that seamlessly integrates recovery, reuse, and recycling — keeping critical minerals in circulation and driving the energy transition. Founded in 2017, we’re delivering low-cost and large-scale energy storage and producing battery materials in the U.S. for the first time, all from batteries we already have.

Essential Duties: 

The Energy Optimization Engineering Intern will support the development of the predictive "intelligence layer" used to manage energy for AI Data Centers and microgrids. Working under the guidance of senior engineers, you will help build and validate time-series forecasting models for GPU power loads and market prices, integrating these inputs into Mixed-Integer Programming (MIP) prototypes. You will collaborate with cloud software teams to test these "forecast-informed" algorithms in a cloud-native environment, assisting in the simulation and backtesting of energy management strategies. Your objective is to help improve the accuracy and efficiency of our EMS, gaining hands-on experience in "value-stacking" and real-world energy optimization. This is a Summer 2026 position.

Responsibilities Will Include: 

AI-Driven Predictive Decision Making and Optimization 

Apply time-series forecasting and machine learning algorithms to predict PV generation, microgrid load profiles, and electricity market prices

Integrate multi-horizon forecasts into intelligent Energy Management Systems (EMS) to drive autonomous decision-making 

Mathematical Modeling & Microgrid Simulation 

Develop high-fidelity mathematical models of Battery Energy Storage Systems (BESS) and Microgrid components

Utilize Mixed-Integer Programming (MIP) and other mathematical optimization techniques to solve complex resource allocation and scheduling problems

Conduct large-scale EMS simulations and scenario testing to validate strategy performance and stability under varying grid conditions 

Cloud Integration & Software Collaboration 

Work closely with Cloud Software Engineers to deploy optimization engines and predictive models into scalable cloud architectures

Design and maintain high-performance APIs for real-time control signals and data exchange between the cloud and site-level assets 

Desired Qualifications: 

MS or PhD in Energy Engineering, Electrical Engineering, Operations Research, Applied Mathematics or a related field

Strong background in optimization (mixed integer, stochastic, robust, convex) with applications to SCUC/SCED or other electricity market problems

Strong background in time series data forecasting applied to energy systems

Excellent first-principles physics understanding of electrical and mechanical systems, power delivery, energy storage and transformation, and basic thermal mechanics

Strong communication and collaboration skills

Familiarity with AI techniques in energy markets 

Physical Requirements:  

Ability to perform essential job functions in compliance with ADA, FMLA, and other relevant federal, state, and local regulations, including meeting both qualitative and quantitative productivity standards

Ability to maintain regular and punctual attendance in line with ADA, FMLA, and applicable standards  

Working Conditions:  

Environment, such as office or outdoors

Ability to work in challenging working conditions which may include exposure to noise, dust, chemicals, and temperature extremes, while protected by PPE, for extended periods of time

Essential physical requirements, such as climbing, standing, stooping, or typing 

In accordance with California pay transparency laws, the salary range for this position is listed below. Actual compensation may vary based on a variety of factors, including experience, education, and skills. 

California Pay Range: $41—$54.50 USD

The position is full-time. Compensation will be commensurate with experience.

 

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