System Modeling Engineer, Energy Storage
Redwood Materials - San Francisco, California, United States
Posted Dec 15, 2025
Benefits
- Parental leave
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- Non-birth-parent leave
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- Family-building benefits
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- Fertility benefits: Not verified
- Adoption assistance: Not verified
- Surrogacy assistance: Not verified
- Mental health support
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- Relocation assistance
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- Childcare support
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- Learning budget
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- Salary
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- 401(k) match
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Schedule
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- Weekend work
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Application
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- Assessment
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- Deadline
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Where they hire
State eligibility is not yet verified.
About this role
System Modeling Engineer, Energy Storage San Francisco, California, United States 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. 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
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