Machine Learning Compiler Engineer

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! We are looking for an engineer with deep expertise in compiler technology, and eager to tackle new challenges and responsibilities as the role evolves. As the position progresses, there will be opportunities to demonstrate leadership, influence key decisions, collaborate with and support other engineers, and help guide the direction of Apple’s AI-driven capabilities across the ecosystem.

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 • 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

Minimum Qualifications

Bachelor’s degree in Computer Science, Computer Engineering, or a related field with 5 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

Bachelor’s (and/or Master's/PhD) degree in Computer Science, Computer Engineering, or a related field with 10 years of relevant experience 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 Proven track record in mentoring and coaching engineers, with an interest in taking on increasing responsibilities and contributing to the team's development

Eeo Content

Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant.