ISE, SIML - Failure Analysis ML Engineer

Santa Clara Valley (Cupertino), California, United States
Machine Learning and AI


Weekly Hours: 40
Role Number:200165402
Do you think Computer Vision and Machine Learning can change the world? Do you think it can transform the way millions of people capture, discover and share the most special moments of their lives? We truly believe it can! The System Intelligence and Machine Learning (SIML) group is responsible for crafting machine learning solutions to extract high level structure information from images, videos and text shipping on all Apple platforms (macOS, iOS, tvOS, watchOS). Examples include face recognition, scene classification, OCR, handwriting recognition as well as the support for internal tools. The group combines research and development in a dynamic and engaging environment. Our data team is responsible for crafting and building high quality datasets at scale. At the heart of machine learning, data defines how Apple features and products operate and what is the final user experience that will impact millions of our customers. This is an exciting time to join us: grow fast, and have an impact on multiple key features on your first day at Apple!

Key Qualifications

  • You have experience in training machine learning models (preferably text or computer vision)
  • You're aware of the challenges associated to building ML datasets and machine learning models (eg face detector): definition and coverage of target data distribution, potential biases, potential failure modes (eg low light, pale/dark skin etc...)
  • You have strong Python coding skills which enable you to manipulate data at scale & to run ML models
  • You have creativity and a good sense of product, which enable you to build tools/frameworks that are impactful and convenient to use by different types of end users
  • You’re ambitious, pragmatic and result focused
  • You show strong communication skills and proactivity


Our team focuses on data collection/generation, smart filtering/selection, annotation, as well as failure analysis (FA). Each year, we power dozens of features and work closely with ML teams across the entire company. Apple's commitment to deliver incredible experiences to a global and diverse set of users in full respect of their privacy leads our team to explore innovative data collection processes. The position focuses on contributing to structure a FA function across SWE, by leading FA operations for key Apple features. This includes: - Define product-centred axes of analysis (eg lighting conditions for images) and associated classes (eg low light < 100 ISO, backlit, ...) relevant to target feature, in collaboration with model DRI and feature DRI - Identify other potential failure modes based on a data driven approach - When applicable, benchmark model using targeted public datasets - Characterise potential biases in training set along chosen axes - Request data collection efforts and/or implement smart pipelines based on advanced ML technology and humans in the loop to create test sets covering the various axes of investigation - Participate in the design of a failure analysis framework that continuously tests successive versions of target model. The infrastructure includes a testing framework, reporting tools & data visualisation, with a web front-end. - Report progress and issues found in technical meetings and sponsor meetings - Suggest mitigation options (data and/or model) and lead mitigation experiments, when issues are found In this position, you will interact with product teams and with R&D DRIs.

Education & Experience

Bachelors or Masters in Computer Science, Mathematics, Physics, or a related field (or equivalent practical experience).

Additional Requirements