AI Test Engineer, Sensing & Connectivity
Apple
- Location
- Onsite (San Diego, California)
- Employment
- Full-time
- Level
- Mid Level
Posted 2 days ago
About the Role
Join Apple's CoreMotion team to build the sensing and intelligence layer for motion-driven experiences across devices. You will design AI-native tooling and agentic workflows to accelerate algorithm development, validation, and synthetic data generation at scale.
Skills
Python
Machine Learning
Artificial Intelligence
LLMs
Agentic Frameworks
Prompt Engineering
Sensor Fusion
Algorithm Development
Data Pipelines
Synthetic Data Generation
Software Engineering
Evaluation Frameworks
Activity Recognition
Distributed Compute
Regression Detection
Full job details
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.
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
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
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
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