Apple

Compiler Tooling Engineer (Neural Engine) - (m/f/d)

Stellenbeschreibung:

Overview

The ANE Software team develops the compiler and runtime for machine learning accelerators on Apple Silicon.

Description

As a compiler tooling engineer in the Apple Neural Engine Software team, you will be expected to

  • Implement software interfacing with the hardware for artificial intelligence applications across a wide range of Apple product platforms
  • Develop compiler optimizations to improve latency/bandwidth of our ML models
  • Collaborate 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

Minimum Qualifications

  • BS and a minimum of 3 years experience with software development
  • Experience with compiler development
  • Excellent programming skills in C++, C or Swift
  • Proficiency in English

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
  • Experience with MLIR
  • Experience in building debugging and performance analysis tooling
  • 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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Stelleninformationen

  • Veröffentlichungsdatum:

    20 Feb 2026
  • Standort:

    München
  • Typ:

    Vollzeit
  • Arbeitsmodell:

    Vor Ort
  • Kategorie:

  • Erfahrung:

    2+ years
  • Arbeitsverhältnis:

    Angestellt

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