Apple
Battery Machine Learning Algorithm Engineer
$175K–$325K
Cupertino, California +1 · Full-time · Posted Oct 22, 2026
- Location
- Cupertino, California
San Diego, California - Experience
- No minimum years specified; preferred qualification: 10+ years relevant industry experience.
- Education
- PhD preferred.
About the job
Develops machine-learning algorithms, control strategies, and embedded implementations to improve battery-system intelligence, runtime, efficiency, and safety.
What you'll do
- Develop and deploy algorithms for battery health, power, and charge estimation, predictive modeling, and real-time battery management.
- Apply physics-informed ML and optimize algorithms for resource-constrained embedded platforms.
- Collaborate with system teams to co-optimize battery algorithms with device power management and thermal systems.
What they ask for
- Experience in machine learning, control theory, and optimization, including the listed methods.
- Experience in MATLAB/Simulink.
- Experience in C/C++ for embedded systems and Python and ML frameworks (PyTorch, TensorFlow).
Nice to have
- PhD and 10+ years relevant industry experience.
- Nonlinear dynamical systems modeling, physics-informed or hybrid physics/ML, or MPC implementation and real-time optimization experience.
Pay
$184,700 and $324,800 (base salary); $175,000 and $308,500 (base salary)
Tools
RNNs, LSTMs, Transformers, MPC, Kalman filters, MATLAB/Simulink, C/C++, Python
AI focus
Develops battery-focused machine learning and physics-informed models, including predictive load and electro-thermal models, and deploys compressed models on embedded platforms.
Model-written summary · the original posting is authoritative