About The Position

Imagine what we could do together. At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job, and there's no telling what we could accomplish! The Apple Services Engineering team is one of the most exciting examples of Apple's long-held passion for combining art and technology. The products we build power the intelligence behind App Store, Apple TV, Apple Games, Apple Music, Apple Podcasts, Apple Books, Apple Sports and Apple Fitness. And we do it on a massive scale, meeting Apple's high standard for quality and excellence, to deliver a huge variety of entertainment in over 50+ languages to more than 150 countries. If you are looking for an opportunity to grow in a technical capacity by leveraging your skills along with building up solid domain knowledge and automated testing strategies and systems around Apple's services offerings in the AI/ML space, we would love to talk to you!

Requirements

  • Bachelor’s degree with a minimum of 5 years, or Master’s degree with a minimum of 3 years, of experience in software development and/or test automation, including at least 3 years leading complex, distributed systems.
  • Proficiency in Java, Python or similar programming languages
  • Experience with planning and execution of validating REST and gRPC APIs
  • Passion for quality engineering and delivering large scale distributed systems
  • Creative problem solving with attention to detail
  • Solid communication skills and ability to collaborate with multiple collaborators
  • Highly organized, creative, self-motivated, and passionate about achieving results.
  • Excited about the possibilities unlocked by AI and ML
  • Advocacy for a positive customer experience

Nice To Haves

  • Knowledge of Big Data systems is a plus
  • Experience with testing or working with AI and/or ML systems is a plus
  • Adept at leveraging technology to solve problems, including building tooling, automating tasks

Responsibilities

  • Define end-to-end test strategy for AI/ML-powered services in partnership with multi-functional stakeholders
  • Author test plans and identify edge cases, failure modes, and risk areas across distributed services and ML lifecycle pipelines
  • Develop and maintain automated API, service-level tests, and validations for data and ML pipelines, as features are being implemented
  • Design and evolve automation frameworks and tooling that scale across teams and product surfaces
  • Apply AI tooling and proof of concept models to build solutions that advance the rigor, coverage, and productivity of quality engineering
  • Drive best practices around quality gates, CI/CD, continuous training, and continuous testing, fostering a culture of built-in quality throughout the SDLC
  • Surface coverage gaps and drive process and architectural improvements across the SDLC through quality
  • Define and track quality metrics such as test coverage, flakiness, and pipeline reliability across systems
  • Mentor junior team members
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