Apple is seeking an engineer to develop innovative machine learning algorithms and control strategies aimed at enhancing battery systems. This role focuses on on-device implementations that improve the utility and intelligence of these systems. The ideal candidate will bring a strong background in machine learning and control theory. Passion and dedication are essential to succeed in this dynamic environment.

• PhD and 3+ years of relevant industry experience
• Experience in machine learning including RNNs, LSTMs, and Transformers
• Experience in control theory and optimization techniques such as MPC and Kalman filters
• Proficiency in MATLAB/Simulink
• Experience in C/C++ for embedded systems and Python with ML frameworks like PyTorch and TensorFlow
• Experience with physics-informed neural networks or hybrid physics/ML approaches
• Experience with MPC implementation and real-time optimization

• Develop novel machine learning algorithms to enhance battery systems
• Implement control strategies for improved system performance
• Conduct mathematical modeling for nonlinear dynamical systems
• Collaborate with cross-functional teams to integrate solutions
• Optimize algorithms for real-time performance on embedded systems

• Employees at Apple are often offered comprehensive benefits that support physical and mental well-being—flexible medical plans, confidential counseling, onsite wellness centers at major campuses, and resources for fitness and daily life. Families typically receive fertility support, paid parental leave with gradual return, caregiving leave, and dependent-care guidance, while financial perks commonly include stock grants (with purchase discounts), 401(k) matching, and income-protection coverage. Employees also see robust time off, Apple University learning and tuition reimbursement, donation matching and paid volunteer hours, and deep product and partner discounts.