Software Quality Assurance Engineer for Machine Learning

3 weeks ago


Cupertino, California, United States Apple Inc. Full time
About the Role

We are seeking a highly skilled Software ML QA Engineer to join our Creativity Apps QA team at Apple Inc. This is an exciting opportunity to work on high-quality iOS and macOS creativity applications and contribute to shaping upcoming products that will delight and inspire millions of Apple's customers.

Key Responsibilities
  • Scripting, parsing data, and working closely with the annotation operations team to ensure the features work end-to-end for customers.
  • Developing and implementing workflow projects, regression testing, and bug filing.
  • Collaborating with other team members to develop requirements, identify appropriate testing implementations processes, and methodologies.
  • Managing priorities, communicating progress, and risk through regular status updates.
Requirements
  • Minimum of 5 years industry experience in quality assurance with a prior focus in Machine Learning.
  • Strong comprehension of machine learning algorithms, supervised and unsupervised modeling techniques.
  • Understanding of the mechanics of machine learning, deep learning, computer vision, natural language processing, and generative AI.
  • Proficient in Python and/or Swift or comparable languages.
  • Meticulous, analytical, methodical, and creative problem-solving ability with a commitment to driving quality forward.
What We Offer

At Apple, we offer a comprehensive compensation package, including base pay, discretionary bonuses, commission payments, and relocation assistance. Our employees also have the opportunity to become Apple shareholders through participation in our discretionary employee stock programs. Additionally, we provide comprehensive medical and dental coverage, retirement benefits, and a range of discounted products and free services.

Apple is an equal opportunity employer that is committed to inclusion and diversity. We take affirmative action to ensure equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics.



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