Apple-posted 2 months ago
Mid Level
Cupertino, CA
5,001-10,000 employees
Computer and Electronic Product Manufacturing

Play a part in the next revolution in human-computer interaction and redefine mobile computing through voice interaction! Apple's Siri AI Quality Engineering team is looking for a hard-working and skilled Machine Learning Engineer to join our mission of delivering premier AI experiences to millions of users worldwide. In this role, you will be instrumental in ensuring the highest quality of Siri by developing and deploying innovative ML solutions for automated testing, anomaly detection, and performance analysis. You will work on a diverse set of problems, from predicting potential regressions to crafting intelligent systems that can identify subtle quality issues before they impact users. In this role, you will apply your expertise in ML, data analysis, and software engineering to drive the strategy and execution of large-scale evaluation efforts for Siri's most sophisticated features. You will collaborate with top engineering, design, and product teams to define quality standards, build automated evaluation pipelines, and deliver insights that guide Siri's development across iPhone, Mac, iPad, Watch, HomePod, Vision Pro, and more.

  • Develop and deploy innovative ML solutions for automated testing, anomaly detection, and performance analysis.
  • Predict potential regressions and craft intelligent systems to identify quality issues.
  • Drive the strategy and execution of large-scale evaluation efforts for Siri's features.
  • Collaborate with engineering, design, and product teams to define quality standards.
  • Build automated evaluation pipelines and deliver insights for Siri's development.
  • Experience in Swift/XCTest/XCUITest is preferred.
  • Excellent problem-solving, analytical, and debugging skills.
  • Experience working with large-scale datasets, infrastructure, and/or data formats (e.g., JSONL, protobuf).
  • Comfortable working in a fast-paced, collaborative environment with shifting priorities.
  • Experience with large-scale data processing (e.g., Spark, Hadoop) is a plus.
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