AIML - Staff Machine Learning Engineer - ML Efficiency, ML Platform & Technology

Do you want to shape the platform that enables the next generation of intelligent experiences on Apple products & services? In Apple's Machine Learning Platform Technology & Infra team, we have built the platform that Apple uses for developing machine learning, artificial intelligence, and computer vision applications. As a team, we have a variety of technical backgrounds, from machine learning PhDs to builders of large-scale production systems.

Specifically in this role, you will be working on optimizing end-to-end system performance of distributed machine learning workloads. This is a highly collaborative role, and you will be working with key partners across the company.

Key responsibilities include:

• Engaging with ML researchers to optimize end-to-end performance of large scale distributed ML workloads
• Analyzing workload metrics to identify sources of inefficiencies and working with users to understand and optimize ML workloads
• Conducting workload analysis based on benchmarking key workloads on deployed systems
• Improving large scale training resiliency by optimizing applications and frameworks for improved recovery from failures and preemptions
• Influencing architecture, design, development, and operations of next generation ML accelerator systems based on workload insights

The ideal candidate will have a deep understanding of machine learning systems and cloud computing infrastructure. This role offers the opportunity to work on cutting-edge technology and shape the future of AI and ML at Apple.