Motion Sensing AI Automation Engineer

The Motion Sensing Hardware team at Apple develops sophisticated AI/ML solutions and automation frameworks that support cutting-edge sensing technologies in consumer products.

This role offers an opportunity to join a team that designs and implements robust software systems enhancing hardware capabilities and providing valuable data insights throughout the product development lifecycle.

We invite motivated and innovative software engineers to help create the intelligent systems that put our products in a class of their own.

As a Motion Sensing Automation Systems Engineer, you will be responsible for architecting and delivering scalable automation and AI/ML solutions tailored to the unique needs of sensing hardware systems.

Your work will focus on developing reusable software components and frameworks for data collection, processing, and analysis, enabling automated testing, failure prediction, and performance optimization of sensor systems.

You will apply expertise in software engineering, machine learning algorithms, and data science to build production-grade tools that transform experimental data into actionable insights, empowering our engineering teams while continuously evolving your technical skills.This position requires strong software development capabilities in modern programming languages, experience with AI/ML frameworks and libraries, and a solid foundation in data structures and algorithms.

You will develop and maintain AI-driven data automation solutions, creating LLM-powered tools and classic data automation pipelines to streamline test execution, data acquisition, analysis, and presentation of results.

The role demands a system architecture mindset that can design flexible, maintainable solutions addressing current needs while anticipating future requirements, excellent communication skills, and a commitment to software quality and best practices.

You will design intelligent interfaces helping motion sensing engineers gather and interpret sensor data in real-time, deploy AI systems for autonomous sensor characterization and data analysis, and build predictive models allowing designers to investigate the impact of varying performance parameters while developing deep familiarity with sensor signal chains and software layers.Degree in Software Engineering, Electrical, Mechatronic or Computer Science Large Language Model (LLM) implementation: Experience integrating LLMs for hardware documentation search, natural language interfaces to hardware diagnostic tools, and automated report generation from test data Familiarity with prompt engineering, fine-tuning, and RAG techniques to make hardware knowledge more accessible to team members through conversational interfaces Experience with neural networks, computer vision for inspection systems, and reinforcement learning for optimization problems Experience integrating ML models into production hardware tools Experience with lab automation frameworks and hardware communication protocols (I2C, SPI, UART, etc.) Experience developing APIs that expose hardware functionality Passion for continuously improving development methodologies and staying current with emerging technologies that can enhance hardware testing and development workflows Collaborative mindset with experience working closely with hardware engineers Familiarity with motion sensing technologies, magnetometers, and environmental sensors Experience with Python, C++, infrastructure, server, firmware, and embedded systems Knowledge of characterization, testing, and signal analysis methodologiesArray