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Software Development Engineer in Test

Job in Seattle, King County, Washington, 98127, USA
Listing for: Apple Inc.
Full Time position
Listed on 2026-02-28
Job specializations:
  • IT/Tech
    AI Engineer, Machine Learning/ ML Engineer, Data Engineer, Cloud Computing
Salary/Wage Range or Industry Benchmark: 139500 - 258100 USD Yearly USD 139500.00 258100.00 YEAR
Job Description & How to Apply Below

Seattle, Washington, United States Software and Services

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. We are the people who power the App Store, Apple TV, 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!

Description

We are seeking an experienced engineer with a passion for quality engineering and a working understanding of AI/ML systems to lead quality efforts across our machine learning platform. In this strategic role, you will shape how we test and validate machine learning pipelines, data workflows, and platform services that power our AI products  will drive end-to-end quality initiatives across data ingestion, model training, deployment pipelines, and MLOps tooling.

As a senior technical leader, you will influence architecture, establish test frameworks tailored for ML systems, and guide teams on scalable, testable, and reliable AI infrastructure.

Responsibilities
  • Lead Quality Strategy for ML Platform:
    Own and define the testing strategy for end-to-end ML pipelines, data flows, and AI platform services.
  • Tooling & Infrastructure Influence:
    Guide the selection and integration of tools and platforms that support scalable test automation, data validation, continuous training (CT), and continuous integration/continuous delivery (CI/CD) in ML workflows.
  • Collaborate with ML Engineers & Data Scientists:
    Partner closely with AI/ML engineers, MLOps, and data science teams to ensure testability, model governance, and validation of ML outputs.
  • Champion Best Practices:
    Define and enforce standards for quality in ML systems — including unit, integration, regression, and fairness testing.
  • Measure & Improve Quality:
    Define and track quality metrics such as test coverage for ML pipelines, test flakiness, and pipeline reliability.
  • Mentor Engineering Teams:
    Influence ML Engineering and Platform teams to adopt a quality-driven approach in their design and implementation.
  • Stay Ahead of AI Testing Trends:
    Explore new tools and research in AI quality assurance, ML testing frameworks, and integrate them where beneficial.
Minimum Qualifications
  • 10+ years in software development and/or test automation, with at least 3 years leading complex, distributed system testing.
  • B.S. in Computer Science or similar field, M.S. preferred.
  • Strong programming experience in Java or Python, with ability to write reusable test frameworks.
  • Proven ability to lead testing efforts for large-scale, backend or platform systems (ideally including microservices or cloud-based architectures).
  • Deep understanding of test design methodologies, CI/CD practices, and test automation at scale.
  • Experience with test frameworks and tools such as PyTest, JUnit, or equivalent.
  • Experience with performance testing of large scale systems.
  • Skilled in driving multi-functional quality programs and influencing engineering architecture and tooling.
Preferred Qualifications
  • Experience testing AI/ML systems or platforms that include ML model training or data pipelines.
  • A general understanding of Machine Learning Lifecycle.
  • Have worked on projects using GenAI.
  • Experience working with cloud platforms (AWS/GCP/Azure) and containerized environments (Docker, Kubernetes).
  • Contributions to quality strategies in AI/ML product teams or research settings.

At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress…

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