ML Data Quality Lead

Apple; Cupertino (CA); On-site; USD 150,000 - 210,000; Full time

Job summary

Apple Inc. is seeking a Data Quality Lead within the Machine Learning Data Ops team to ensure high-quality datasets powering AI features across iPhone, iPad, Mac, Apple Watch, and AirPods.

You will own data quality for your portfolio, design checks, and lead analysts, collaborating with R&D, data engineers, and vendors. You will build and extend QA tooling, including review interfaces and data pipelines, leveraging AI-assisted development to deliver reliable, scalable data products for ongoing

Qualifications

• Bachelor's degree or equivalent practical experience.
• 4+ years of experience in ML data operations, data quality, or a comparable data-centric quality function.
• Working proficiency in Python for data manipulation and reporting.
• Hands-on experience using AI coding assistants to build working QA tools or analysis.
• Strong written and verbal communication skills.

Responsibilities

• Owns the quality strategy and roadmap across the data request life cycle, defining workflows and controls.
• Translates ambiguous quality expectations into explicit standards and rules for vendors and teams.
• Runs QA checks across pilot and production phases and validates trends before datasets reach R&D.
• Designs and builds new QA tools and extends review interfaces and data pipelines using AI-assisted development.
• Introduces model-assisted checks into review workflows and measures agreement against human labels.
• Verifies analyses, metrics, and generated artifacts independently before publication.
• Leads internal and external quality analysts and presents findings to project teams and vendors.
• Partners with Collection, Annotation, and R&D teams to pin down project specs and ensure unambiguous guidelines.

Skills

Python

Data QA

QA tooling

Communication

Education

Bachelor's degree

Job description

Apple Inc. is seeking a Data Quality Lead within the Machine Learning Data Ops team to ensure high-quality datasets powering AI features across iPhone, iPad, Mac, Apple Watch, and AirPods.

You will own data quality for your portfolio, design checks, and lead analysts, collaborating with R&D, data engineers, and vendors. You will build and extend QA tooling, including review interfaces and data pipelines, leveraging AI-assisted development to deliver reliable, scalable data products for ongoing