The Graphics Games and Machine Learning Test Engineering organization is seeking an expert self-motivated Software Tools and Automation Engineer with a real passion for making the GPU and graphics experience on our products the best it can be. You will work with emerging gpu technologies at Apple in ensuring that we successfully bring these technologies to our customers in the industry leading bar that weve this role you will primarily focus on the development and execution of test automation to support both new HW and SW features. You will develop novel ways to test the software components that make up the gpu driver stack and think of creative ways to expand the automation. As a successful candidate you should have a strong aptitude for learning new technologies excellent interpersonal skills and the ability to drive sophisticated and challenging collaboration with other engineering teams and an ability to thrive under pressure are key skills required to succeed in this role.
Bachelors degree in Computer Science Computer Engineering or a related technical field or equivalent practical experience.
Proven experience in software development with a focus on tools and test automation.
Proficiency with Unix-based operating systems (e.g. Linux macOS) and command-line interface (CLI) tools.
Experience in Python. Swift is a plus.
Strong debugging troubleshooting and analytical skills.
Knowledge of fundamental data structures algorithms and software design principles.
Familiarity with the complete software development life cycle (SDLC) including requirements design development testing and deployment.
Experience with version control systems (e.g. Git).
Masters degree or PhD in Computer Science Computer Engineering or a related technical field.
Proven experience in developing and maintaining QA infrastructure and automation frameworks.
Experience with C/C programming.
Familiarity with continuous integration/continuous deployment (CI/CD) pipelines and tools.
Experience with white-box testing methodologies and code coverage analysis.
Knowledge of system-level debugging and performance analysis tools.
Understanding of computer architecture and low-level hardware interaction.
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