Munich Electrification - Battery Science & Data Engineer (f/m/d)
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Requirements
• University degree in electrical / control engineering, physics, applied mathematics, or a similar field. • Strong background in battery physics, aging mechanisms, and state estimation fundamentals. • Proficiency in Python for data analysis and scientific computing (NumPy, SciPy, Pandas). • Experience designing and evaluating diagnostic or estimation algorithms for electrochemical systems. • 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. • Excellent communication skills in English; proficiency in German is a strong plus. • Ideally, you also have • Experience with electrochemical impedance spectroscopy (measurement, interpretation, modeling). • Experience applying machine learning to time-series or sensor data (classification, anomaly detection). • Familiarity with embedded constraints; awareness of what is realistic on a microcontroller vs. what belongs in the cloud. • Published work or thesis in battery diagnostics, electrochemical methods, or related fields. • 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.
Responsibilities
• 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. • 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.
Benefits
• 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 • Trust-based working hours and hybrid work • 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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