AIML - Quality Engineering Manager, Data Operations

Apple Inc.; Cupertino (CA); On-site; USD 173,000 - 261,000; Full time

Job summary

An innovative firm is seeking a Quality Engineering Manager to lead a team focused on data quality and QA processes. In this pivotal role, you will manage quality assurance strategies, refine processes, and collaborate with cross-functional teams to enhance data quality. Your leadership will drive continuous improvement in methodologies and tools, ensuring the highest standards in data operations. If you have a passion for data quality and a knack for leading teams, this opportunity is perfect for you.

Benefits

Medical Coverage

Retirement Plans

Educational Reimbursements

Bonuses

Relocation Assistance

Stock Programs

Qualifications

• 7+ years in data quality or quality engineering, with 2+ years in management.
• Exceptional leadership and communication skills required.

Responsibilities

• Manage a team of Quality Engineers for QA strategy and tooling.
• Conduct root cause analyses on quality issues and drive corrective actions.

Skills

Leadership Skills

Data Quality Concepts

Analytical Skills

Problem-Solving Skills

Communication Skills

Tools

Python

SQL

Job description

AIML - Quality Engineering Manager, Data Operations

Cupertino, California, United States | Machine Learning and AI

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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 related fields, including 2+ years in management or leadership roles.
• Exceptional leadership, communication, and organizational skills.
• Meticulous with strong analytical and problem-solving skills.
• Knowledge of data quality concepts, challenges, and best practices.
• Proven track record of process improvements and managing cross-functional initiatives.

Preferred Qualifications

• Experience with AI/ML/LLM, understanding ML model development cycles and the importance of human-labeled data.
• Experience with large-scale data operations or data-centric ML infrastructure.
• Knowledge of data quality standards, frameworks, and governance.
• Experience designing automated QA checks and quality monitoring systems.
• Strong data analysis skills; proficiency with scripting languages (e.g., Python) and data tools (e.g., SQL).

At Apple, base pay is part of our total compensation and depends on skills, qualifications, experience, and location. The range for this role is $173,100 to $260,400.

Employees may participate in stock programs, receive benefits like medical coverage, retirement plans, discounts, educational reimbursements, bonuses, and relocation assistance. Learn more about Apple Benefits.

Apple is an equal opportunity employer committed to diversity and inclusion. We promote equal opportunity regardless of race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other protected characteristics. Learn more about your EEO rights as an applicant.