**Role Number:** 200629659-3956
**Summary**
At Apple, we're on the cutting edge of delivering transformative experiences through Artificial Intelligence. If you're passionate about pushing the boundaries of AI and hardware optimization, we want you to join our team! As a Machine Learning Compiler Engineer on the Apple Neural Engine (ANE) team, you'll work to bring high-performance, low-power AI solutions to life on iconic Apple products like the Vision Pro, iPhone, iPad, Mac, and more. This is a dynamic opportunity to work with us in a creative, collaborative environment while developing groundbreaking technologies that will shape the future of computing.
Are you ready to help us deliver the next groundbreaking Apple products?
**Description**
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
• 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
**Minimum Qualifications**
+ Bachelor’s degree in Computer Science, Computer Engineering, or a related field with 3 years of relevant experience
+ Experience with program analysis and IR (Intermediate Representation), or programming language design, particularly with MLIR and LLVM
+ Proven expertise in compiler design and architecture, including deep experience with front-end and middle-end optimizations, register allocation, and back-end code generation
+ High-level proficiency in C++ and experience working with large, complex software systems
**Preferred Qualifications**
+ Master's or PhD degree in Computer Science, Computer Engineering, or a related field
+ Demonstrated ability to ship high-quality production software
+ Strong communication skills and ability to collaborate effectively across teams and functions
+ Experience optimizing compilers for distributed, parallel, or heterogeneous execution environments, with a solid understanding of shared memory, synchronization, and multi-threading techniques
+ Expertise in neural network inference on specialized SoCs or GPUs, and knowledge of deep learning frameworks and tools
+ Familiarity with Just-in-Time (JIT) compilation and dynamic optimization techniques for real-time code execution