**Role & seniority: ** AI/ML Engineer (CoreMotion team); senior/experienced implied by requirements for production shipping and end-to-end delivery

**Location & work type: ** Not specified in text

**Stack / tools (implied): **

Python (core software engineering)
LLMs (prompt engineering, LLM-based workflows)
Agentic frameworks (agentic system building)
ML evaluation tooling (metrics, quality frameworks, regression detection)
Foundation models / multimodal ML
Distributed compute & large-scale data infrastructure (preferred)

**Top 3 responsibilities: **

Build AI-native tooling and agentic workflows to accelerate motion-algorithm development and validation
Scale evaluation to millions of sensor sessions via AI-orchestrated replay, dataset selection, scheduling, and regression detection
Create agentic data pipelines for ingest/curation/quality checks; use LLMs for synthetic sensor data and to accelerate annotation

**Must-have skills: **

Strong ML/AI system building and shipping experience (production or major projects)
Hands-on LLM expertise (prompting + agentic frameworks)
Solid software engineering fundamentals in Python
Ability to design evaluation frameworks, quality metrics, and test infrastructure
Cross-functional delivery of end-to-end features on release schedules

**Nice-to-haves: **

Experience with sensor data, motion al

Full Description

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.

DESCRIPTION

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

MINIMUM QUALIFICATIONS

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

PREFERRED QUALIFICATIONS

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

AI Test Engineer, Sensing & Connectivity

Full Description