External Job · via Greenhouse

System Modeling Engineer, Energy Storage

redwoodmaterialsSan Francisco, CA

💰 $165,000 – $225,000/yrFull-timeelectricianhandyman

Quick Summary

System Modeling Engineer focusing on developing multiphysics modeling platforms for novel energy storage system design at Redwood Materials.

Skills & Keywords

Multiphysics modelingEnergy storagePython/MATLABSystem design

Responsibilities will include

Contribute to Redwood Material’s in-house performance and technoeconomic model.
Drive architectural studies to explore the cost and performance design space.
Produce component-level sensitivity analysis to allow component owners to make globally optimal cost and performance tradeoffs.
Utilize the models to produce repeatable and dependable results for various stakeholders within the organization to drive product architecture and site-specific deployment decisions.
Parallelize our modeling framework to utilize cloud computing resources to get results faster.
Lead model validation efforts by writing test plans, working with test engineers to execute the test, and using the data to correlate the model.
Effectively communicate modeling results to drive architecture and performance initiatives.

Desired Qualifications

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.

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

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An MS or PhD in Mechanical Science, Electrical Engineering, or a related field. Or a BS and 2+ years of related work experience.
Excellent first-principles physics understanding of electrical and mechanical systems, power delivery, energy storage and transformation, and basic thermal mechanics.
Experience collaborating in software projects with multiple contributors.
Hybrid or electric powertrain model development, PV model development, or data analysis in Python or MATLAB/Simulink.
Familiarity with basic controls techniques, such as filters, PID controllers, and system identification.
Experience with optimization techniques.
Demonstrated ability to write clear and testable engineering requirements.
Strong communication and collaboration skills.