Machine Learning Compiler Engineer

1 Month ago • All levels • Research Development • $175,800 PA - $312,200 PA

Job Summary

Job Description

As a Machine Learning Compiler Engineer, you will architect and develop the compiler for Apple's proprietary Neural Engine Accelerator. This involves optimizing for deep learning inference, focusing on performance, scalability, and power efficiency. Collaboration with cross-functional teams, including hardware and platform architecture teams, is crucial to bring new hardware silicon to market and ensure compiler support for next-generation features. The role includes leading the design and implementation of complex compiler features, mentoring engineers, and defining new compiler architecture approaches. The role contributes to improving the scalability and general performance of AI workloads on Apple hardware and promotes a culture of learning and collaboration.
Must have:
  • Architect and develop the compiler for Apple's Neural Engine Accelerator.
  • Optimize compiler for deep learning inference.
  • Collaborate with cross-functional teams.
  • Design and implement complex compiler features.

Job Details

As a Machine Learning Compiler Engineer, you will: • Architect and develop the compiler for Apple's proprietary Neural Engine Accelerator, optimizing it for deep learning inference with a focus on performance, scalability, and power efficiency • Collaborate with cross-functional teams, including hardware and platform architecture teams, to bring new hardware silicon to market and ensure compiler support for next-gen features • Lead the design and implementation of complex compiler features, advancing both technical capabilities and strategic alignment across the team and company • Mentor and guide emerging and mid-level engineers, sharing expertise to foster their growth in compiler technologies and ensuring high standards of code quality, innovation, and efficiency • Play an instrumental role in defining new compiler architecture approaches and optimizations, balancing trade-offs between performance, energy efficiency, and hardware constraints • Identify and drive initiatives that will improve the scalability and general performance of AI workloads on Apple hardware, contributing to the vision and roadmap of the Apple Neural Engine team • Cultivate a culture of learning and collaboration, encouraging innovation, and supporting engineers in their development, with the potential to expand influence across the organization

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