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

Apple • Santa Clara, CA

109d

About The Position

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.

Requirements

• Experience working with large scale parallel and distributed accelerator-based systems
• Experience optimizing performance and AI workloads at scale
• Experience developing code in one or more of training frameworks (such as PyTorch, TensorFlow or JAX)
• Strong communicator with ability to analyze complex and ambiguous problems
• Programming and software design skills (proficiency in C/C++ and/or Python)
• Experience working in a high-level collaborative environment and promoting a teamwork mentality
• Bachelor's degree in Computer Science and 7+ years of work experience

Nice To Haves

• Deep understanding of computer systems and the interactions between HW and SW
• Experience in performance analysis and optimization experience in Cloud accelerators
• Advanced degree in CS

Responsibilities

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

What This Job Offers

• Career Level: Senior
• Education Level: Bachelor's degree
• Number of Employees: 5,001-10,000 employees