Lead Compiler Engineer (Neural Engine) - m/f/d
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About the Role
The ANE Software team develops the compiler and runtime for machine learning accelerators on Apple Silicon
Description
As a lead compiler engineer in the Apple Neural Engine Software team, you will be expected to -
Analyze, design and implement software interfacing with the hardware for artificial intelligence applications across a wide range of Apple product platforms
Assume technical leadership, mentor and guide other developers - Ensure technical excellence and robust, maintainable software
Design and develop compiler optimizations to improve latency/bandwidth of our ML models - Develop software across our compiler, framework, driver and firmware
Collaborate closely with model teams to support new machine learning models on our hardware
Conduct performance profiling and diagnostics using and developing specialized tools
Engage with QA teams
Preferred Qualifications
MS or PhD in computer science, machine learning or related field
Experience in low level software architecture, modeling or validation
Familiarity with AI networks for example CNN, transformer and diffusion model architectures and their performance characteristics
Proficiency with profiling and optimizing complex software
Experience with SoC low level software development, distributed computing or hardware acceleration
Strong background in data science and statistical methods, with demonstrated ability to analyze large datasets and present complex insights clearly
Experience with MLIR
Experience in building debugging and performance analysis tooling
Minimum Qualifications
BS and a minimum of 10 years experience with system software development
Experience with compiler development
Excellent programming skills in C++, C or Swift
Proficiency in English
Strong written and verbal communication skills
At Apple, we’re not all the same. And that’s our greatest strength. We draw on the differences in who we are, what we’ve experienced, and how we think. Because to create products that serve everyone, we believe in including everyone. Therefore, we are committed to treating all applicants fairly and equally. We will work with applicants to make any reasonable accommodations.
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