This role involves engineering improvements in stability and performance for Apple's Private Cloud Compute, which powers generative AI. The team focuses on building scalable frameworks primarily in Swift, while also utilizing C++ for hardware integration. Engineers will collaborate with hardware, product, and research teams to implement new functionalities and optimize the ML inference stack. The environment is collaborative, valuing expertise and quality output.

• 2 years of practical experience in a relevant field or equivalent practical experience.
• Bachelor's degree in Computer Science, Computer Engineering, or a related field.
• Experience building large-scale distributed systems that serve ML inference.
• Strong knowledge of systems or server languages such as Python, Go, Rust, Java, or C++.
• Experience with low-level systems programming or hardware/SoC bring-up.
• Strong debugging and observability skills with experience in logs, metrics, and traces.
• Depth in ML inference serving optimizations such as quantization and GPU acceleration.

• Engineer continuous improvements in stability and performance for Private Cloud Compute.
• Implement new functionalities as they emerge from the research community.
• Integrate inference code into a full service stack for reliable user traffic handling.
• Distribute and coordinate ML inference across different SoCs and multi-node clusters.
• Collaborate with cross-functional teams to extend the inference stack to new platforms.

• 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.