Deep Learning Compiler Engineer
Posted 2025-05-31
Remote, USA
Full-time
Immediate Start
- As a Deep 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
- Proven expertise in compiler design and architecture, including deep experience with front-end and middle-end optimizations, register allocation, and back-end code generation
- Experience with program analysis, IR (Intermediate Representation), and programming language design, particularly with MLIR and LLVM
- High-level proficiency in C++ and experience working with large, complex software systems
- Bachelor’s degree in Computer Science, Computer Engineering, or a related field, with 3 years of experience shipping production software
- 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
Core Skills: Deep Learning
Other Skills: Hardware
Seniority: Junior, Mid, Senior
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