Posted: Mar 21, 2025
Role Number:200591547
Would you like to contribute to generative AI and transform how people interact with AI technologies? Do you believe Machine Learning and AI can change the world? We truly believe it can! We are the ML Data Ops Team within the software engineering organization at Apple. We are responsible for building high-quality ML datasets at scale, used to train ML models that power AI-centric features for many Apple products (iPhone, iPad, Mac, Apple Watch, and even AirPods). Such features go from the smart wallpaper on your iPhone Lock Screen to the models that highlight the faces of your loved ones in your Photos app to input experiences (e.g., autocorrect, next-word prediction, handwriting recognition). We are looking for a Quality Analyst who demonstrates exceptional attention to detail and a deep focus on quality. Someone passionate about Apple products and values, who loves collaborating and working with data ops at scale, and who is committed to the hard work necessary to improve data quality for our R&D partners continuously. We invite you to join us at this exciting time! Grow fast and positively impact multiple critical features on your first day at Apple!
As part of the ML Data Ops QA team, you’ll play a central role in enhancing Apple’s customer experience by reviewing and verifying that all datasets supplied to R&D are complete, accurate, and consistent. We are committed to data excellence, ensuring diversity, relevance, and integrity in our datasets to enable ML engineers to build AI solutions that are transformative, ethical, and impactful. Each year, we power dozens of features and work closely with ML teams across the entire company. In this position, you’ll be accountable for setting up workflows and examining assets and labels of incoming datasets, ensuring that any data delivered to R&D meets Apple’s rigorous quality standards. You’ll work in a fast-paced, dynamic, technology-focused environment leveraging generative AI technologies to help evaluate data in partnership with a QA project manager. You’ll review the Annotation Analyst evaluations and become the subject matter expert in your camera domain. You’ll lead training for the annotators and provide quality feedback to the QA project managers overseeing the project. You’ll use your analytical skills to track and report trends. You’ll collaborate with team members and share ideas for business improvements. At Apple, our individual backgrounds, perspectives, and passions help us build the ideas that move all of us forward. We’ll train you to be an expert in understanding, supporting, and improving the data quality experience.
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $30.35 and $49.10/hr, and your base pay will depend on your skills, qualifications, experience, and location.
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple’s discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple’s Employee Stock Purchase Plan. You’ll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses — including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits.
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote 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. Learn more about your EEO rights as an applicant.
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