Battery Science & Data Engineer
Role details
Job location
Tech stack
Job description
We are looking for a driven engineer to join our Battery Science and Data team and own an exploratory diagnostic workstream. You will investigate what advanced battery diagnostics can add to our Battery Management Systems - starting with state estimation of internal battery states and building toward fault and anomaly detection. Working on our lab demonstrators with real BMS hardware, you will evaluate diagnostic methods hands-on and translate findings into algorithm concepts that feed into our product pipeline.
The position sits within a small, focused pre-development team that validates new concepts before they reach SW engineering or cloud deployment. Your work connects to the team's broader efforts in cloud analytics, edge inference, and safety-critical detection algorithms. You define the "how" - we set the direction together.
Your future tasks at a glance
- You are the owner of an exploratory workstream and not executing against a fixed spec. You define the technical direction, work hands-on in the lab, and your success is measured by the transition of lab-proven concepts into our real-world BMS product pipeline.
- Design and evaluate advanced diagnostic algorithms for state estimation and battery health assessment across cell chemistries (NMC, LFP).
- Develop novel fault detection and anomaly detection approaches, combining physics-based features with machine learning.
- Build validation frameworks that quantify algorithm performance across operating conditions, temperatures, and aging states.
- Define data collection requirements like measurement protocols and operating points needed for robust validation.
- Collaborate with research partners on joint algorithm development and structure research project with academic partners.
Requirements
Do you have experience in SciPy?, Do you have a Doctoral degree?, * University degree in electrical / control engineering, physics, applied mathematics, or a similar field.
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Strong background in battery physics, aging mechanisms, and state estimation fundamentals.
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Proficiency in Python for data analysis and scientific computing (NumPy, SciPy, Pandas).
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Experience designing and evaluating diagnostic or estimation algorithms for electrochemical systems.
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Comfortable working without a fixed playbook; define your own experiments, critically evaluate results, value negative outcomes, and change direction when the data tells you to.
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Excellent communication skills in English; proficiency in German is a strong plus. Ideally, you also have
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Experience with electrochemical impedance spectroscopy (measurement, interpretation, modeling).
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Experience applying machine learning to time-series or sensor data (classification, anomaly detection).
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Familiarity with embedded constraints; awareness of what is realistic on a microcontroller vs. what belongs in the cloud.
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Published work or thesis in battery diagnostics, electrochemical methods, or related fields.
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Experience with battery test equipment and lab measurement setups. Note on level: We are primarily looking for a Senior candidate. However, we encourage exceptional PhD graduates with a strong focus on battery diagnostics or state estimation algorithms to apply; for these candidates, we offer a contributor path with increased mentorship during the first months.
Benefits & conditions
The chance to be part of a highly innovative, agile, and unique team with prestigious customers in the automotive and battery storage sector. You will gain a deeper knowledge around connected & electric vehicle batteries, battery management and electronics development and strive in an exciting work environment
Benefits (Full-time Employees):
- Trust-based working hours and hybrid work
- Adequate and competitive compensation
- Pension Plan/Bonus
- Free access to the fitness center right next to us or subsidized EGYM Wellpass
- Free snacks, coffee, drinks and lunch (freshly cooked by our chef) every day
- Public transport ticket
- Bike-Leasing via Business Bike
- Experience various inspiring and fun team events
- ME-branded clothing
- Option to "work from anywhere" (6 weeks/year)
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