Fawkes Energy is building the next generation of battery intelligence platforms for electric vehicles and energy storage systems. Our systems turn raw battery data into deep insights on health, safety, performance, and residual value using a combination of electrochemical understanding, physics-based models, and machine learning.
We are looking for an exceptional problem solver who can translate complex battery behaviour into robust algorithms that work on real-world field data. You will work at the intersection of electrochemistry, battery modeling, and software engineering to build production-grade models for battery health and diagnostics.
Responsibilities
- Develop algorithms for battery health diagnostics and prognostics
- Build and implement battery models (ECM, ROM, electrochemical abstractions)
- Interpret large-scale battery datasets (pack and cell voltages, current, temperature, SOC etc.)
- Extract features and signatures from field data to infer degradation and faults
- Develop optimization routines for parameter estimation
- Translate physics understanding into robust production-ready code
- Build scalable Python implementations that integrate into cloud analytics systems
- Work closely with the product and engineering team to deploy models in real-world systems
Must have skills:
- Understanding of Li-ion electrochemistry and degradation mechanisms
- Experience interpreting battery voltage/current/temperature data
- Familiarity with battery models (ECMs, ROM, simplified electrochemical models)
- Experience with optimization, parameter estimation, or system identification
- Strong Python programming skills
