Job Description
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 are the Audio Product System Quality team, and we are seeking a creative and motivated Software Engineer in Test to join our team for advanced audio products like AirPods/AirPods Pro/AirPods Max! You will be a key part of the hardware/software development process and have the opportunity to work closely with firmware/software/hardware teams while we deliver the best audio experience for our customers. To achieve this, it requires building large automated frameworks to gather thousands of iterations of test data weekly, and we need people like you to help us build and maintain our tools for critical functional, stability and performance testing of AirPods products.
You'll plan, design and write code for system automation with an emphasis on hardware and firmware-centric risks across a number of devices. You will be at the nexus of hardware, firmware and software where you work cross-functionally with multiple engineering and QA/QE 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!
As a Software Engineer in Test you will be responsible for the development of key new areas for AirPods functional, stability and performance test coverage, enhanced by machine learning capabilities while also balancing the day-to-day operations of existing automation that runs thousands of iterations daily.
Preferred Qualifications
Experience with hardware/firmware/software validation, hardware/firmware/software integration, or testing methodologies
Experience with Claude code or other AI tools, MCPs and skills
Background in data science, machine learning, computer vision, or statistical data analysis
Knowledge of real-time audio or Bluetooth technologies
Familiarity with data analysis and visualization tools such as Tableau or Superset
Minimum Qualifications
Bachelor's degree in Computer Science, Computer Engineering, or Electrical Engineering
2 years experience involving machine learning algorithms and their practical applications
Professional work experience testing embedded systems
Hands-on programming experience with Python
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
