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Apple ISE, SIML - Data Annotation Lead in Cupertino, California

ISE, SIML - Data Annotation Lead

Santa Clara Valley (Cupertino),California,United States

Machine Learning and AI

  • At least one year experience in data annotation

  • Highly organized with strong attention to detail

  • Capacity to multitask and manage several projects in parallel, meet deadlines and provide visibility to client and partners

  • Ability to define/design/develop/optimize annotation workflows and QA workflows (anticipate potential failure modes and edge cases, detect anomalies, generalize, synthesize)

  • Problem solving & critical thinking capacities, with an eye for innovation and for continuous optimization (improve the diversity and quality of assets, reduce time to delivery and cost)

  • Understanding of the challenges associated to building datasets for machine learning R&D (eg coverage, bias)

  • Excellent communication and interpersonal skills


Our team focuses on data collection/generation, smart filtering/selection, annotation, as well as failure analysis. 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. This position focuses on setting up and managing annotation projects (in-house, outsourced) and on ensuring the quality of the data delivered to R&D. This includes: Communicate with R&D team to understand expectations and define specs of annotation tasks Participate in selection of assets to be included in the dataset Define annotation workflow (and re-assess it over time), establish guidelines and training material, establish range for time per task Calibrate task with vendor Define and continuously adjust QA methodology (eg types of errors, penalties, QA workflow) Lead QA effort Track quantities and quality delivered

Education & Experience

Bachelors degree in: Photography, Graphics Design, Computer Science, Mathematics, Physics, or equivalent experience

Additional Requirements

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