Battery Machine Learning Algorithm Engineer

What you'll do

• Develop ML algorithms for State of Health, State of Power, and State of Charge estimation.
• Build predictive models of user load patterns and coupled electro-thermal dynamics.
• Design advanced control algorithms and multi-objective optimization frameworks for real-time power delivery.
• Develop physics-informed ML approaches to combine physics-based models with data-driven methods.
• Deploy algorithms on resource-constrained embedded platforms using quantization, pruning, and distillation.
• Implement fixed-point arithmetic and fallback mechanisms for sensor noise and missing data.

What we're looking for

• Experience in machine learning (RNNs, LSTMs, Transformers), control theory, and optimization (MPC, Kalman filters, convex/nonconvex optimization).
• Experience in MATLAB/Simulink.
• PhD and 3+ years of relevant industry experience (preferred).
• Mathematical modeling experience for nonlinear dynamical systems (preferred).
• Experience in C/C++ for embedded systems and Python & ML frameworks like PyTorch or TensorFlow (preferred).
• Experience with physics-informed neural networks or hybrid physics/ML approaches (preferred).
• Experience with MPC implementation and real-time optimization (preferred).