Software Engineer - Test and Validation

Apple • Austin, TX

1d

About The Position

We are 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. This role involves building large automated frameworks to gather thousands of hours of test data weekly, and maintaining tools for critical stability testing of Mac and Home products. The engineer will plan, design, and write code for system stability automation with an emphasis on hardware-centric software risks, simultaneously running on a large number of systems. The role is at the nexus of hardware and software, requiring cross-functional collaboration with engineering and QA teams to identify risk areas, develop testing responses, and support engineering investigations. Artificial intelligence and machine learning are expected to be core to the work, developing next-generation automation tools that predict, prevent, and optimize critical system failures before they impact customers. As a Software Engineer, you will be responsible for the development of key new areas of Mac and Home stability test coverage enhanced by machine learning capabilities, while also balancing the day-to-day operations of existing automation that runs on thousands of units daily.

Requirements

• Bachelor's degree in Computer Science, Computer Engineering, or Electrical Engineering
• 2 years experience involving machine learning algorithms and their practical applications
• Hands-on programming experience with Python
• Exposure to one or more ML frameworks (PyTorch, TensorFlow, or JAX)
• Familiarity with software engineering fundamentals (version control, testing, debugging)
• Strong problem-solving skills and ability to work in a cross-disciplinary team environment
• Excellent written and verbal communication skills

Nice To Haves

• Experience with hardware/software validation, hardware/software integration, or testing methodologies
• Background in data science, machine learning, computer vision, or statistical data analysis
• Exposure to CoreML, Swift, or iOS/macOS development through coursework or projects
• Familiarity with data analysis and visualization tools such as Tableau or Superset
• Project or research experience applying ML to anomaly detection, predictive maintenance, or test optimization

Responsibilities

• Help design and implement automated stress and stability tests for embedded systems, with hardware-centric focus
• Contribute to ML-powered test automation frameworks and validation tools
• Analyze validation/test data and help build predictive models that detect issues early
• Write and update problem reports, including ML-assisted analysis of failures and root causes
• Collaborate with cross-functional engineering and QA teams to learn the broader testing landscape
• Adapt to rapid project schedules and shifting priorities common in new-product development

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level