Applied Machine Learning Engineer, Platform Architecture at Apple

Department: Hardware

Compensation · Listed in posting

$184,700 – $277,600

Location: Cupertino, California
Level: not_specified
Posted: Aug 17, 2026

Description

Apple is hiring an AI/ML Engineer to build and apply machine learning and generative AI workflows for analyzing workload data and exploring System-on-Chip architectures. The role focuses on performance and power behavior across fabric, memory, caches, voltage and frequency control, clock and power gating, sleep states, and bottleneck prevention. The engineer will translate insights into hardware and software changes, partner with silicon and operating-system teams, validate changes on real silicon, and support products through shipping.

Required Skills

Deep learning
Generative AI
Python
Time-series analysis
Feature engineering
C/C++

Additional Information

Minimum Education: Bachelor of Science in Computer Science, Computer Engineering, Electrical Engineering, or a related field
Required Previous Experiences: Applied machine learning industry experience deploying complex machine learning systems in production
Experience applying modern machine learning techniques to large real-world datasets
Programming experience in Python and modern deep learning frameworks
Preferred Qualifications: Working knowledge of SoC compute, memory, and power-management subsystems and C/C++ modeling infrastructure
Depth in time-series analysis and feature engineering on streaming telemetry
Experience applying machine learning beyond prediction, including decision-making, policy optimization, and large configuration-space search
Track record of training large-scale models across distributed clusters
Experience building stateful, multi-turn agentic frameworks and complex execution flows
Master of Science or Ph.D. in a relevant field and 10+ years of relevant experience
Track record of moving quickly from hypothesis to result and iterating based on evidence
Excellent communication and collaboration skills across technical disciplines

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