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Form Energy is a climate technology company developing long-duration iron-air battery systems for grid-scale energy storage. The company has secured contracts with major US utilities and is ramping production at a manufacturing facility in West Virginia.
As a Senior Fluids Analysis Engineer, you will own computational fluid dynamics (CFD) and transient thermal modeling for Form Energy's 100-hour iron-air battery systems, spanning from R&D through full commercial deployment. Your work will directly inform architectural strategies and design details for the Electrolyte, Thermal, Hydrogen, and Air Delivery Systems, ensuring safe and predictable grid-scale operation.
Key responsibilities include:
- Develop high-fidelity CFD and transient thermal models across multiple physical scales, from micro-scale electrochemical cell fields to macro-scale containerized systems
- Validate numerical physics-based models against empirical data in collaboration with test and instrumentation teams
- Build automated simulation and optimization workflows to evaluate fluid routing, pressure drops, and cooling loop efficiencies
- Partner with electrochemical, mechanical, and power electronics teams to resolve complex thermal-fluid integration challenges
- Select appropriate simulation methodologies, mesh structures, and boundary conditions to identify thermal risks and hot spots
- Standardize internal modeling workflows and establish rigorous peer design reviews
- Identify gaps in physics-based toolsets and develop customized tools to unblock engineering development
You will work on mission-critical systems that directly impact grid stability and the transition to clean energy. The role offers relocation assistance and is based in Berkeley, CA.
REQUIREMENTS:
- Bachelor's degree with 5+ years of related work experience, OR Master's degree with multiple years of experience, OR PhD in thermal-fluid sciences with industry experience
- Deep expertise in commercial CFD codes and meshing software (Ansys Fluent, Star-CCM+, Comsol Multiphysics)
- Strong foundational knowledge of conjugate heat transfer, fluid dynamics, multiphase flow, and closed-loop cooling systems
- Applied experience with Python or MATLAB for post-processing, visualization, and automation of multi-physics datasets
- Demonstrated ability to translate complex simulation results into actionable system-level design requirements
- Ability to build cross-functional networks and achieve technical alignment on multi-variable design trade-offs
- Intellectual curiosity and pragmatic problem-solving skills to navigate design ambiguity while balancing modeling fidelity with execution speed
