Machine Learning System Software Engineer

At Apple, we're revolutionizing AI experiences through the Apple Neural Engine (ANE) team. As a Machine Learning System Software Engineer, you'll be at the forefront of developing high-performance, low-power AI solutions for iconic products like Vision Pro, iPhone, iPad, and Mac.

The role focuses on architecting and optimizing system runtime software for Apple's proprietary Neural Engine Accelerator. You'll work closely with hardware and platform teams to bring new silicon to market, while leading complex system runtime features development. Your expertise in system software technology will be crucial in balancing performance, energy efficiency, and hardware constraints.

Key responsibilities include mentoring other engineers, driving architectural decisions, and improving AI workload scalability across Apple's ecosystem. You'll collaborate with cross-functional teams to advance both technical capabilities and strategic alignment, while fostering a culture of innovation and learning.

The position offers opportunities to shape the future of AI computing at Apple, with increasing responsibilities in technical leadership and team development. You'll work in a creative, collaborative environment, contributing to groundbreaking technologies that will define the next generation of Apple products.

Ideal candidates bring deep expertise in software design, strong C/C++ skills, and experience with complex software systems. Understanding of neural network inference, distributed computing, and hardware optimization is highly valued. This role combines technical excellence with leadership opportunity, perfect for those passionate about pushing the boundaries of AI and hardware optimization.

Benefits include competitive base pay ($181,100-$318,400), equity opportunities, comprehensive healthcare, retirement benefits, education reimbursement, and various Apple-specific perks. Join us in delivering transformative AI experiences that will shape the future of computing across Apple's entire product line.