About The Position

The CoreMotion team builds the sensing and intelligence layer that powers motion-driven experiences across Apple products, from device attitude and heading to fitness tracking and gesture recognition. We're looking for someone who thinks natively in AI: fluent with modern LLMs, agentic systems, and building at scale. You'll bring AI-first approaches to hard problems in a domain where the signals are physical and the scale is hundreds of millions of devices. As a member of our dynamic group, you will have the rewarding opportunity to craft upcoming products that will delight and inspire millions of Apple's customers every single day.

Requirements

  • B.S. in Computer Science or relevant field
  • Experience building and shipping ML or AI systems, in production or through significant project work
  • Hands-on experience with LLMs, prompt engineering, and agentic frameworks
  • Strong software engineering fundamentals, with proficiency in Python and comfort across the stack
  • Experience designing evaluation frameworks, quality metrics, and test infrastructure
  • Demonstrated ability to work cross-functionally and deliver end-to-end features against release schedules

Nice To Haves

  • Experience with sensor data, motion algorithms, or embedded ML systems
  • Familiarity with distributed compute platforms and large-scale data infrastructure
  • Background in algorithm validation, simulation, or synthetic data generation

Responsibilities

  • Design and deploy AI-native tooling and agentic workflows to accelerate algorithm development and validation across motion sensing domains
  • Scale algorithm validation to millions of sensor sessions using AI-orchestrated replay, with automated dataset selection, evaluation scheduling, and regression detection
  • Build agentic data pipelines to ingest, curate, and quality-check motion datasets, and use LLMs to generate synthetic sensor data and accelerate ground-truth annotation
  • Define benchmarks that measure model quality, reliability, and real-world behavior
  • Apply modern ML techniques, including foundation models and multimodal approaches, to motion sensing, sensor fusion, and activity recognition
  • Partner with hardware, apps, and platform teams to ship AI-driven experiences from the ground up
  • Own the quality bar for motion features and turn the latest AI capabilities into real impact for users
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