Battery Machine Learning Algorithm Engineer
Summary
Develops novel machine learning algorithms, control strategies, and on-device implementations to improve the intelligence and utility of Apple's battery systems. Daily work combines ML (RNNs, LSTMs, Transformers) with control theory and optimization (MPC, Kalman filters) using MATLAB/Simulink, C/C++, and Python ML frameworks.
Envision what you could do here. At Apple, we believe new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish.
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.
Minimum Qualifications
- Experience in machine learning (RNNs, LSTMs, Transformers), control theory and optimization (MPC, Kalman filters, convex/nonconvex optimization)
- Experience in MATLAB/Simulink
Preferred Qualifications
- PhD and 3+ years relevant industry experience
- Mathematical modeling experience for nonlinear dynamical systems
- Experience in C/C++ for embedded systems and Python & ML frameworks (PyTorch, TensorFlow)
- Experience with physics-informed neural networks or hybrid physics/ML approaches
- Experience with MPC implementation and real-time optimization