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.
Description
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.","responsibilities":"Develop and maintain AI-driven data automation solutions for the Motion Sensing team
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Create and implement LLM-powered tools and classic data automation pipelines to streamline test execution, data acquisition, analysis, and presentation of results
Develop intelligent interfaces that help motion sensing engineers gather and interpret sensor data in real-time
Design and deploy AI systems that can assist in characterizing motion sensors, autonomously analyze and mine the resulting data, and generate insights to be presented to cross-functional teams
Drive root cause analysis of failures through AI-powered data analysis and visualization
Build procedures and AI-powered tools that unify and automate the way sensor data is gathered and analyzed
Use machine learning techniques on gathered test data to build predictive models for sensors that allow designers to investigate the impact of varying different performance parameters
Develop deep familiarity with sensor signal chains and software layers
Build proof-of-concept AI solutions and participate in showcasing and evaluating newest ideas
Track the adoption and effectiveness of AI and automation solutions, continuously refining them based on user feedback and evolving requirements from motion sensing engineering teams
Work closely with hardware engineers to understand their needs, translate technical requirements into software solutions, and iterate based on feedback
Preferred Qualifications
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 methodologies
Minimum Qualifications
BS and a minimum of 3 years relevant industry experience
Data visualization and analysis: Development of tools for real-time data monitoring, statistical analysis of hardware performance metrics, and interactive dashboards for hardware teams
Experience with data processing pipelines and storage solutions for large hardware datasets
Strong object-oriented programming skills: Demonstrated proficiency in designing modular, extensible software architectures using OOP principles
Ability to create reusable component libraries, implement inheritance hierarchies for hardware abstractions, and develop clean interfaces between system components
Machine learning integration expertise: Experience applying classical ML techniques (regression, classification, clustering) to hardware performance data and sensor outputs
Ability to develop and deploy predictive maintenance tools, anomaly detection systems, and automated calibration solutions using established ML frameworks (scikit-learn, TensorFlow, PyTorch)
Understanding of fundamental AI/ML concepts and their practical applications in hardware contexts
Strong software architecture and development skills: Proficiency in multiple programming languages suitable for both low-level hardware interaction and high-level application development
Commitment to producing robust, maintainable, and well-documented tools that follow team coding standards
Excellent written and verbal English communication skills, particularly the ability to explain software concepts to hardware specialists and translate hardware requirements into software specifications
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant .
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