Machine Learning Compute Efficiency Lead, Infrastructure & Planning
Apple · Cupertino, CA · Machine Learning and AI
About this role
Apple is hiring a senior-level ML Platform Engineer in the machine learning function based in Cupertino, CA. The posting calls out experience with Kubernetes, PyTorch, Machine Learning.
- Role
- ML Platform Engineer
- Function
- machine learning
- Level
- senior
- Track
- Individual contributor
- Location
- Cupertino, CA
- Department
- Machine Learning and AI
- Posted
- Apr 23, 2026
More roles at Apple
Job description
from Apple careersApple’s Platform Acceleration & Compute Efficiency (PACE) is a high-leverage team operating at the critical intersection of our ML organizations, underlying compute infrastructure, and core platform tooling. Our mission is to empower Apple’s software engineering teams with efficient, scalable compute. By driving out operational friction and optimizing the broader machine learning ecosystem, we directly accelerate the pace of development across the company.
As foundation models become increasingly central to Apple's user experiences, maximizing the efficiency of our ML compute is paramount. In this role, you will focus relentlessly on compute efficiency, ensuring that Apple’s models run as fast, reliably, and cost-effectively as possible. You will tackle massive optimization challenges, from maximizing hardware utilization across GPUs, TPUs, and custom Apple Silicon, to shaping workload scheduling and capacity allocation for large model serving.