AIML - Sr. Software Engineer - ML Efficiency, Machine Learning Platform & Technology

$207,800 - $312,200/Yr

Apple - Cupertino, CA

Full-time - Mid Level

Cupertino, CA

Computer and Electronic Product Manufacturing

About the position

The role involves optimizing end-to-end system performance for distributed machine learning workloads within Apple's Machine Learning Platform Technology & Infra team. The position requires collaboration with machine learning researchers and key partners across the company to enhance the efficiency and resiliency of large-scale ML applications.

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

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

Benefits

• Comprehensive medical and dental coverage
• Retirement benefits
• Discounted products and free services
• Reimbursement for certain educational expenses including tuition
• Discretionary bonuses or commission payments
• Relocation assistance