Apple is seeking an engineer to develop innovative machine learning algorithms and control strategies aimed at enhancing battery systems. This role involves creating on-device implementations that improve the utility and intelligence of these systems. The ideal candidate will bring a wealth of experience in machine learning and control theory. A strong background in mathematical modeling and real-time optimization is essential for success in this position.

• PhD and 10+ years of relevant industry experience
• Experience in machine learning techniques such as RNNs, LSTMs, and Transformers
• Proficiency in control theory and optimization methods including MPC and Kalman filters
• Experience with MATLAB/Simulink
• Proficiency in C/C++ for embedded systems and Python with ML frameworks like PyTorch and TensorFlow
• Experience with mathematical modeling for nonlinear dynamical systems
• Familiarity 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
• Create on-device implementations for battery intelligence
• Collaborate with cross-functional teams to integrate solutions
• Conduct mathematical modeling for nonlinear dynamical systems
• Apply physics-informed neural networks and hybrid approaches in projects
• Optimize real-time performance of battery 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.