Hardware System Validation Engineer

Apple•San Jose, CA

15h

About The Position

Join the system validation team at Apple's Hardware Engineering, where we validate system-level performance of Apple SoCs and other key modules (cameras, displays, and other state-of-the-art sensors) in a system environment that mirrors real product use.

Requirements

Bachelor's degree or higher in Engineering or a related field
3+ years of experience with hardware/software architecture and interoperability of complex systems
Scripting proficiency in Python; comfortable building and maintaining automation frameworks
Experience in one of the following: hardware system design and integration, SoC design/integration, debug/testing, or validation

Nice To Haves

Experience with SoC bring up, familiar with computer architectures (cache, memory hierarchy, data pipelines) and logic design
Experience with bringing-up and testing of camera, display or any other modules in consumer electronics
Experience in silicon validation software engineering or related field
Experience with embedded system debug
Experience with lab equipment such as oscilloscopes and thermal chambers
Strong proficiency in Python and Lua; proficient in Shell scripting.
Familiarity with industry standards (USB, PCIe, DDR, etc.)
General software development experience (Python, C++, log review, code review)
Strong communication and collaboration skills

Responsibilities

Primarily validate Apple SoCs, while also running testing on other modules such as cameras, displays, and sensors that ship in Apple products
Work closely with module designers and functional test writers to understand high-level architectures of each IP block within Apple SoCs or other modules, and define applicable validation plans
Develop and execute these system tests, leveraging scripts and automation frameworks, on a large volume of engineering prototypes throughout the product life cycles
Serve as the first line of debug when issues occur — triaging, isolating, and bucketizing failures
Partner with domain experts to define DoEs (Design of Experiments), develop root-cause theories, and test possible workarounds
Development of automated testing for power consumption data collection from our battery and power supply systems
Creation of new test methodologies to expand test coverage to new modalities including optical / computer-vision based testing
Optimize test and calibration flows for hardware sub-systems.
Apply AI/ML techniques for test data mining, anomaly detection, and factory data analytics
Travel internationally ~10% of the time