Camera Software QA Engineer

Santa Clara Valley (Cupertino), California, United States


Role Number:200198534
We are looking for an experienced and results-oriented Software Quality Engineer to ensure that we deliver the best in-class camera solution in all Apple products. You will be focused on testing the firmware/driver for core hardware components such as the image processing pipeline and the machine learning neural engine. You will work closely with software development team to create and execute test plans focused on qualifying camera firmware and drivers to ensure we ship a quality product. You must comfortable working in a dynamic environment and possess a strong aptitude for learning new technologies. You should have a history of working on successful, large-volume consumer products.

Key Qualifications

  • Highly motivated and passionate about SW QA testing
  • Minimum of 3 years of previous QA experience with testing embedded system products
  • Experience with hardware/software development lifecycle
  • Programming in Python, shell and MATLAB. Experience programming in C/C++ is a plus
  • Exposure to CI process and tools such as Jenkins
  • Strong written and verbal communication skills. Strong data analysis skills
  • BONUS: Deep understanding of the camera technologies, image signal processing (ISP) pipeline, 3A , video formats and color spaces. An interest in digital photography is a plus


In this role you will: - Design test cases and execute test plans related to functionality, performance, power, stability, and image quality of our camera solution. You should be able to describe and clearly document test plan/procedure/test results and assess the quality of releases - Automate test cases and develop test tools on mobile platforms and Macs. You will use continuous integration environments/tools and CI standard methodologies to enhance test coverage. - Partner with development teams and multi-functional QA teams to triage, diagnose, debug issues and derive root-cause. You should be identify trends and highlight potential risks.

Education & Experience

BS or MS in Computer Science or Electrical Engineering

Additional Requirements