On-Device ML Quality Infra Engineer - Graphics & Games

Apple Inc.; Cupertino (CA); Vor Ort; USD 185.000 - 325.000; Vollzeit

Benefits dieser Stelle

Stock awards

Relocation assistance

Zusammenfassung

Apple Inc. is seeking an On-Device ML Quality Infrastructure Engineer for the Cupertino-based team.

You will design and maintain build systems and CI/CD pipelines for the On-Device ML stack, and develop automation frameworks for testing across functional, regression, and integration scenarios. You will contribute to robustness through fuzz testing, performance profiling, and regression tracking, partnering with ML, compiler, and hardware teams to meet their needs and accelerate validation

Qualifikationen

• Bachelor's degree in Computer Science or relevant discipline.
• Strong experience with build systems (CMake, Bazel) and CI/CD.
• Strong programming skills in Python.
• Deep knowledge of quality practices and test automation.

Aufgaben

• Design, build, and maintain build systems and CI/CD pipelines for the On-Device ML stack.
• Develop and maintain automation frameworks for testing (functional, regression, integration).
• Contribute to robustness initiatives including fuzz testing across stack components.
• Track and investigate performance regressions and work with teams to resolve.
• Identify gaps in testing coverage and tooling and drive improvements.

Kenntnisse

Build systems & CI/CD

Python programming

Quality assurance practices

Collaborative communication

Ausbildung

Bachelor's degree in CS or related field

Master's degree in CS or related field

Tools

CMake

Bazel

CI/CD tooling

Jobbeschreibung

Apple Inc. is seeking an On-Device ML Quality Infrastructure Engineer for the Cupertino-based team.

You will design and maintain build systems and CI/CD pipelines for the On-Device ML stack, and develop automation frameworks for testing across functional, regression, and integration scenarios. You will contribute to robustness through fuzz testing, performance profiling, and regression tracking, partnering with ML, compiler, and hardware teams to meet their needs and accelerate validation