Apple
Battery Machine Learning Algorithm Engineer
Hybrid · Cupertino, California, United States
Employer posted October 22, 2026
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What the role needs
- We are looking for an engineer who will develop novel machine learning algorithms, control strategies, and on-device implementations to improve the utility and intelligence of battery systems.
- Experience in machine learning (RNNs, LSTMs, Transformers), control theory and optimization (MPC, Kalman filters, convex/nonconvex optimization)
- Experience in MATLAB/Simulink
- Experience in C/C++ for embedded systems and Python & ML frameworks (PyTorch, TensorFlow)
- PhD and 10+ years relevant industry experience
- Mathematical modeling experience for nonlinear dynamical systems
- Experience with physics-informed neural networks or hybrid physics/ML approaches
- Experience with MPC implementation and real-time optimization
From the employer
We are looking for an engineer who will develop novel machine learning algorithms, control strategies, and on-device implementations to improve the utility and intelligence of battery systems. Experience in machine learning (RNNs, LSTMs, Transformers), control theory and optimization (MPC, Kalman filters, convex/nonconvex optimization) Experience in MATLAB/Simulink Experience in C/C++ for embedded systems and Python & ML frameworks (PyTorch, TensorFlow) PhD and 10+ years relevant industry experience Mathematical modeling experience for nonlinear dynamical systems Experience with physics-informed neural networks or hybrid physics/ML approaches Experience with MPC implementation and real-time optimization
Availability and requirements can change. Confirm details with the employer before applying.