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Apple Machine Learning Compiler Engineer United States, California, Sunnyvale 768369573
21.04.2025
As a Machine Learning Compiler Engineer, you will:- 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
- 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
- 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
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.
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