AIML - Quality Engineering Manager, Data Operations
Cupertino, California, United States
Machine Learning and AI
Summary
Posted: May 05, 2025
Weekly Hours: 40
Role Number: 200602201
We are seeking a Quality Engineering Manager to lead and guide a team focused on ensuring the quality of data used for training and evaluating machine learning models. This role is critical in shaping the processes, tools, and standards that underpin high-quality training data. It combines data analysis, technical mentorship, and operational execution to strengthen our quality assurance systems and drive impact at scale. The ideal candidate is comfortable navigating complexity, collaborating multi-functionally, and making data-driven decisions that directly influence model performance.
Description
Manage and support a team of Quality Engineers responsible for QA strategy, tooling, and implementation across annotation workflows. Define and refine scalable processes and metrics to assess the quality, consistency, and relevance of labeled data. Partner with Engineering teams to build automated validation logic for detecting inconsistencies and data anomalies. Collaborate with Data Scientists and ML Engineers to analyze how data quality impacts model behavior and identify opportunities for data improvement. Lead multi-functional alignment on annotation QA standards and ensure feedback loops between quality, guidelines, and tooling. Own and evolve golden set evaluations, consensus grading protocols, and annotator quality tracking mechanisms. Conduct root cause analyses on quality issues and drive corrective actions in collaboration with upstream teams. Stay ahead of QA and data quality best practices, and drive continuous improvement in tools and methodologies.
Minimum Qualifications
7+ years of experience in data quality, quality engineering, or a related field, including 2+ years in a management or leadership role.
Extraordinary leadership, communication, and organizational skills.
Meticulous, strong analytical and problem-solving skills
Knowledge of data quality concepts, challenges, and best practices
Proven track record of driving process improvements and managing multi-functional initiatives.
Preferred Qualifications
Experience with AI/ML/LLM. Familiarity with ML model development cycles and the role of human-labeled data in training and evaluation.
Experience with large-scale data operations or data-centric ML infrastructure.
Knowledge of data quality standards, frameworks, and governance best practices.
Experience designing and implementing automated QA checks and quality monitoring systems.
Strong data analysis skills; experience with scripting languages (e.g., Python) and data tools (e.g., SQL).
Pay & Benefits
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 $173,100 and $260,400, 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. (https://www.apple.com/careers/us/benefits.html)
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 (https://www.eeoc.gov/sites/default/files/2023-06/22-088\EEOC\KnowYourRights6.12ScreenRdr.pdf) .
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 (https://www.eeoc.gov/sites/default/files/2023-06/22-088\EEOC\KnowYourRights6.12ScreenRdr.pdf) .
Apple will not discriminate or retaliate against applicants who inquire about, disclose, or discuss their compensation.
Apple participates in the E-Verify program in certain locations as required by law.Learn more about the E-Verify program (https://www.apple.com/jobs/pdf/EverifyPosterEnglish.pdf) .
Apple is committed to working with and providing reasonable accommodation to applicants with physical and mental disabilities. Reasonable Accommodation and Drug Free Workplace policy Learn more .
Apple is a drug-free workplace. Reasonable Accommodation and Drug Free Workplace policy Learn more .
Apple will consider for employment all qualified applicants with criminal histories in a manner consistent with applicable law. If you're applying for a position in San Francisco, review the San Francisco Fair Chance Ordinance guidelines applicable in your area.
It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.
