Siri - Software Quality Engineer, Machine Learning and Automated Systems

Seattle, WA
  • Job Code


Posted: Jun 1, 2019

Weekly Hours: 40

Role Number: 200007293

Would you like to play a part in ensuring the quality of groundbreaking technology for large scale systems, natural language, big data, and artificial intelligence? Drive the quality of the Siri user experience and work with the people who built the intelligent assistant that helps millions of people get things done - just by asking. Join the Siri QE team at Apple!

The Software Quality Engineer, Machine Learning and Automated Systems, will own test automation roadmap, ML testing strategy and test tools vision for Siri, ensuring the most optimal testing coverage. Tool requirements fulfillment includes 'proof of concept' development. This role is also responsible for developing the approach, tools and testing for Systems Integration (client/server and data/server). As the Siri architecture evolves, test infrastructure must keep up. A key deliverable of the role is a significant improvement in failure actionability. This is a fast-paced role with high visibility, impact, and ensures we build the most advanced systems in the industry

Key Qualifications

  • 10+ years of professional work experience in Development or Quality Engineering
  • Ideal candidate has experience with test infrastructure, quality tools and automation, and system integration testing
  • Self-motivated and dedicated with proven creative and critical thinking capabilities
  • Experience working with large scale server software features, detailed test planning, design, and execution
  • Advanced programming skills in Java or similar OO language such as C++, Python, Obj-C or Swift
  • Advanced scripting skills in Python, Perl, Bash
  • Working experience with various logging and analytics frameworks
  • Ability to build test automation frameworks from the ground up
  • Experience with root cause analysis of multi-tiered, client-server environments
  • Testing server backend services, especially at the API or protocol level
  • Experience with testing machine learning systems and neural networks
  • Knowledge of statistics based testing approaches, ML training pipelines and accuracy improvements of ML systems
  • Strong organizational skills and experience working on large multi-functional teams
  • Thrives on working in a fast-paced environment with rapidly changing priorities
  • Ability to develop long term vision and execute strategies at scale


You will own the quality engineering automation roadmap for Siri Assistant, ML/NL, and Intelligence features. You will develop QE tool requirements, inclusive of 'proof of concept' development, and co-own the development roadmap. You will define success criteria for QE testing tools and ML testing strategy. The ideal candidate will implement a feedback loop that includes usage data to ensure relevant and accurate test suites accounting for statistics-based testing approach to measure improvements in accuracy. Own Systems Integration testing, complete with test plan and tools development (client/server and data/server)
We are looking for a professional to measure and report the impact of platform changes, think strategic and create ways to evaluate and improve Siri user experience. Lastly, you will drive the team to work towards this shared goal of success automation by improved test coverage, optimization of execution, and improved user experience

Education & Experience

BS/BA in Computer Science or equivalent work experience

Additional Requirements

  • Apple is an Equal Opportunity Employer that is committed to inclusion and diversity. We also take affirmative action to offer employment and advancement opportunities to all applicants, including minorities, women, protected veterans, and individuals with disabilities. Apple will not discriminate or retaliate against applicants who inquire about, disclose, or discuss their compensation or that of other applicants

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Siri - Software Quality Engineer, Machine Learning and Automated Systems

Apple, Inc.
Seattle, WA

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