Streaming Media QE Web Automation Engineer, Graphics, Games, and ML
Apple
- Location
- Onsite (Cupertino, California)
- Employment
- Full-time
- Level
- Senior Level
Posted 2 days ago
About the Role
Apple's Web Streaming Quality Engineering team builds robust automation frameworks to validate high-fidelity media playback across Apple Music, Apple TV+, and partner applications. The role focuses on ensuring seamless user experiences across diverse web platforms and hardware.
Skills
Python
JavaScript
TypeScript
Test Automation
E2E Testing
CI/CD
Web Automation
Streaming Protocols
HLS
Debugging
Network Profiling
Video Quality Assessment
Software Development
Quality Engineering
Test Strategy
Full job details
The Web Streaming Quality Engineering team at Apple ensures our customers enjoy seamless, high-fidelity playback experiences when watching movies, shows, and listening to music across Apple Music, Apple TV+, and third-party partner applications on various web platforms (browsers, smart TVs, connected devices, and game consoles).
We uphold the high bar of quality Apple is known for while building the next generation of web-based streaming infrastructure. We are looking for a strong Python or JavaScript/TypeScript developer to design, build, and maintain our web automation framework and test suites.
We are seeking an experienced Quality Engineering Automation Engineer with strong software development skills in Python and JavaScript/TypeScript to join our team. In this role, you will collaborate closely with engineering, QA, and product teams to design resilient automation systems that validate media playback, streaming performance, and user experience across diverse web environments and hardware platforms. If you are passionate about solving complex automation challenges with robust, scalable solutions, this is the role for you.
Strong software development experience in Python or JavaScript / TypeScript Proven track record in test automation framework design and creating end-to-end (E2E) automated test suites Solid understanding of CI/CD pipelines and building resilient, non-flaky test automation Experience authoring comprehensive test plans and test strategy documentation Strong analytical, debugging, and problem-solving skills BS/MS in Computer Science, Computer Engineering, Electrical Engineering, or equivalent practical experience
Experience with web automation tools/frameworks Familiarity with the HLS streaming protocol (Knowledge of Dash wouldn’t help the team Diagnose, isolate, and debug complex streaming, playback, and network-related issues across streaming clients Knowledge of web performance metrics, network profiling, and video quality assessment techniques
Description
We are seeking an experienced Quality Engineering Automation Engineer with strong software development skills in Python and JavaScript/TypeScript to join our team. In this role, you will collaborate closely with engineering, QA, and product teams to design resilient automation systems that validate media playback, streaming performance, and user experience across diverse web environments and hardware platforms. If you are passionate about solving complex automation challenges with robust, scalable solutions, this is the role for you.
Minimum Qualifications
Strong software development experience in Python or JavaScript / TypeScript Proven track record in test automation framework design and creating end-to-end (E2E) automated test suites Solid understanding of CI/CD pipelines and building resilient, non-flaky test automation Experience authoring comprehensive test plans and test strategy documentation Strong analytical, debugging, and problem-solving skills BS/MS in Computer Science, Computer Engineering, Electrical Engineering, or equivalent practical experience
Preferred Qualifications
Experience with web automation tools/frameworks Familiarity with the HLS streaming protocol (Knowledge of Dash wouldn’t help the team Diagnose, isolate, and debug complex streaming, playback, and network-related issues across streaming clients Knowledge of web performance metrics, network profiling, and video quality assessment techniques