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Über diese Sr. System Modeling Engineer, Energy Storage Stelle bei Redwood Materials

Redwood Materials · Vor Ort · San Francisco, California, United States

About Redwood Materials

Redwood Materials was founded in 2017 by JB Straubel, co-founder and former CTO of Tesla, on a simple but radical idea: the critical minerals powering the energy transition already exist. They just need to come back. Today Redwood is the largest lithium-ion battery recycler in North America — recovering, refining, and redeploying critical minerals from end-of-life batteries back into the supply chain. On the energy side, Redwood has deployed the largest second-life battery project in the world, delivering power to AI data centers in months rather than years using proprietary energy architecture engineered entirely in-house. The company is profitable, the market it operates in is projected to grow 20 to 50 times over the next decade, and Redwood is the only company with the supply chain, the technology, and the operational scale to lead it.

System Modeling Engineer, Redwood Energy 

You will be an early member of a new engineering team, taking a hands-on role in the design, development, and integration of a new product. This position focuses on developing Multiphysics modeling platform to drive the system design of a novel energy storage system. These models must be robust enough to support multiple users, but agile enough to quickly drive a diverse array of design decisions. 

The ideal candidate is highly self-driven, adaptable to a startup environment, and eager to take on novel technical challenges. If you’re excited about working in a dynamic, fast-paced setting within a new department at Redwood, we want to hear from you! 

If necessary, the job level will be adjusted to suit the applicant’s experience and responsibilities. 

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: 

  • 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. 

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:
$162,500—$215,000 USD

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

 

We collect personal information (PI) from you in connection with your application for employment with Redwood Materials, including the following categories of PI: identifiers, personal records, professional or employment information, and inferences drawn from your PI. We collect your PI for our purposes, including performing services and operations related to your potential employment. If you have additional privacy-related questions, please contact us at [email protected].

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