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Apple • San Diego, California, United States
Role & seniority
Stack/tools
Languages: Python, C++, (low- and high-level development)
ML: scikit-learn, TensorFlow, PyTorch; ML pipelines and model deployment
Data: data processing pipelines, real-time visualization, dashboards
Systems: OOP architectures, reusable component libraries, hardware interfaces (I2C, SPI, UART)
AI/automation: LLMs, AI-driven data automation, predictive maintenance and anomaly detection
Hardware sense data: sensor signal chains, motion sensing technologies, magnetometers, environmental sensors
Top 3 responsibilities
Architect and deliver scalable automation and AI/ML solutions for sensing hardware systems
Develop reusable software components/frameworks for data collection, processing, analysis, automated testing, and result presentation
Deploy AI systems for autonomous sensor characterization, data analysis, predictive models, and real-time data interpretation
Must-have skills
BS degree and at least 3 years of relevant industry experience
Strong software architecture and modular design using OOP
Experience with data visualization/real-time dashboards and large hardware datasets
ML integration for hardware data (regression, classification, clustering); predictive maintenance and anomaly detection
Proficiency in multiple languages for hardware interaction and application development
Excellent communi
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.
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
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
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