About the job
Do you want to make a positive impact on the direction of new, key technologies in consumer products while pioneering the future of intelligent quality assurance? We're seeking a creative and motivated Software Engineer to join our Product Systems Quality team, working to ensure world-changing Mac and Home products are delivered at the highest quality to all our customers! To achieve this, it requires building large automated frameworks to gather thousands of hours of test data weekly, and we need people like you to help us build and maintain our tools for critical stability testing of Mac and Home products. You’ll plan, design and write code for system stability automation with an emphasis on hardware-centric software risks simultaneously run on a large number of systems. You will be at the nexus of hardware and software where you work cross-functionally with several engineering and QA teams to identify risk areas and testing responses, and to support engineering investigations. We expect artificial intelligence and machine learning to be at the core of the work, developing next-generation automation tools that predict, prevent, and optimize critical system failures before they impact customers. Come join our team!
Responsibilities
Design and implement on-the-fly automated stress and stability hardware-centric software tests for embedded systems
Design and implement ML-powered test automation frameworks and validation tools
Understand the context where an application will be deployed, providing insights to potential failures
Write and update problem reports enhanced with ML analysis that explains issues, predicts root causes, and provides data-driven recommendations for fixes
Analyze large volumes of validation/test data and build predictive models to detect issues early
Thrive in uncertain, rapid project schedules, being able to quickly shift priorities, maximize testing time, and deploy AI solutions that adapt to changing requirements
Ensure scalability, reliability, and maintainability of systems in production environments
Work with cross-functional teams to help collect and define requirements for AI-enhanced tools, automation, and intelligent reporting systems
Provide training on a regular basis and mentor others as needed
Qualifications
Minimum
Bachelors degree in CS/CE/EE and a minimum of 5 years relevant industry experience
Solid understanding of machine learning algorithms and their practical application
Knowledge of hardware/software validation, hardware/software integration, or testing methodologies
Strong programming skills and hands-on experience with Python
Experience with CoreML, Swift, and iOS/macOS machine learning development
Experience with relevant ML frameworks (PyTorch, TensorFlow, or JAX)
Experience building robust and scalable tools, frameworks and automation systems
Strong problem-solving skills and ability to work in a cross-disciplinary team environment
Excellent written and verbal communication skills
Preferred
Strong verbal and written communication skills
Academic background in data science, machine learning, computer vision, and statistical data analysis
Experience in data analysis and developing data visualizations & reporting with tools such as Tableau or Superset
Experience applying ML to anomaly detection, predictive maintenance, or test optimization