Battery Modeling Engineer

Zipline•South San Francisco, CA

1d•$130,000 - $165,000

About The Position

You will be part of Zipline’s Systems Modeling Team, which develops physics-based models used to architect, optimize, and validate Zipline’s aircraft hardware and operational systems. Battery performance, charging behavior, and lifetime directly affect how reliably the fleet can serve customers. You will own end-to-end battery modeling from cell electrochemistry through pack electro-thermal behavior and fleet software integration. Your work will guide cell selection, hardware operating limits, charging decisions, and the validated energy models used in fleet optimization.

Requirements

5+ years of professional battery-modeling experience, or a PhD plus 2 years, with a focus on electrochemical modeling.
Deep knowledge of cell electrochemistry, heat transfer, thermodynamics, electrical circuits, numerical methods, and optimization.
Hands-on experience with SPM, SPMe, P2D, equivalent-circuit models, and battery degradation mechanisms.
Experience planning, running, or interpreting battery characterization and validation testing, including EIS, HPPC, OCV, and aging studies.
Proficiency in at least one of MATLAB, Python, Julia, C++, or Rust.
Ability to communicate complex model behavior and datasets clearly and work closely with mechanical, electrical, test, and systems-modeling engineers.

Nice To Haves

Advanced degree (MS or PhD preferred) in Mechanical Engineering, Electrical Engineering, Chemical Engineering, Physics, Computational Science, or related field.
Familiarity with PyBaMM or similar electrochemical battery modeling frameworks.
Experience with battery degradation and lifetime modeling.
Experience developing battery state estimation algorithms.

Responsibilities

Own cell-level models across electrochemical and equivalent-circuit fidelities to evaluate performance, fast charging capability, degradation, and lifetime.
Define Zipline’s cell electrochemistry roadmap and lead cell benchmarking and selection with internal teams and cell vendors.
Design and analyze characterization and validation campaigns, including EIS, HPPC, OCV, and cycle and calendar aging studies.
Develop pack-level electro-thermal models that predict electrical and thermal non-uniformity during high-power operation and charging.
Build state-estimation and controls-oriented algorithms for SOC, SOH, SOE, SOP, and aging-aware charging-current limits.
Integrate validated battery and energy models into simulation and operational software that informs fleet charging, turnaround, battery-health, and aircraft-energy decisions.