QA Automation Engineer - Apple Neural Engine (ANE)

About the role

You will be responsible for crafting test cases and implementing test plans related to functionality, performance, power, and stability of the Apple Neural Engine. You will also be responsible for developing and maintaining automation scripts, debugging hardware related issues, and developing new automation test cases. You should be able to describe and clearly document test plan/procedure/test results and assess the quality of releases. You will use continuous integration environments/tools and CI standard methodologies to improve test coverage. You will partner with development teams and multi-functional QA teams to triage, diagnose, debug issues and derive root-cause. You will positively influence the team on testability and bug prevention strategies.

Requirements

• Experience with crafting system and feature level test plans and test cases
• Experience with software development life cycle, testing methodologies and processes
• Strong written and verbal communication skills
• Bonus: Familiarity with Objective-C/Swift, Xctest and XCode IDE
• Bonus: Familiarity with Jenkins
• BS and a minimum of 3 years relevant industry experience
• Experience in hardware related testing
• Experience in test automation and tool development
• Experience in python and shell scripting","internalDetails":null
• Pay & Benefits
• Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

Additional Information

We are looking for an experienced and versatile QA Engineer to ensure that we deliver the best in-class machine learning solution for all Apple products. You will be passionate about testing the ANE software, developing automation frameworks and tools for validating core components that are part of Apple Intelligence Framework. You will work closely with software development team to build and implement test plans focused on qualifying ANE software to ensure we ship a quality product. You must be comfortable working in a dynamic environment and possess a strong interest in learning new technologies. You should have a history of working on successful, large-volume consumer products.

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