Head of Responsible AI Quality & Safety

Apple, Inc.; Cupertino (CA); On-site; USD 238,000 - 402,000; Full time

Benefits offered by this job

Comprehensive medical and dental

Retirement benefits

Discounted products and free services

Educational expense reimbursement

Discretionary bonuses or relocation

Job summary

Apple in Cupertino, CA, invites applications for AIML - Quality Engineering Manager in Responsible AI and Safety. You will lead Apple's Quality Platform Engineering to deliver fast, trustworthy safety signals across all platforms and devices, while building a strong team and culture.

Strong background in ML evaluation and productionML, cross-platform testing, and experience hiring technical teams are required.

Qualifications

• 5+ years of technical team leadership or management experience.
• Experience with ML evaluation, production ML systems, or test/CI infrastructure at scale.
• Strong engineering skills and production-quality code experience (Python or similar).
• Experience across multiple platforms or hardware form factors.
• Experience with human-labeled or crowd-sourced evaluation data, including label noise and inter-rater agreement.

Responsibilities

• Hire, grow, and build the culture of a team spanning test engineering, applied ML, and platform-specific expertise.
• Own leadership reporting and safety sign-off representation for Quality Platform Engineering.
• Set and reprioritize feature clusters and platforms the team covers based on risk and coverage gaps.
• Drive investment in test pipeline efficiency and fast pre-merge signal.
• Extend safety testing coverage to all platforms and devices Apple ships.

Education

MS or PhD in Computer Science, Machine Learning, Statistics, or related field

Tools

Python

CI/CD pipelines

Job description

Apple in Cupertino, CA, invites applications for AIML - Quality Engineering Manager in Responsible AI and Safety. You will lead Apple's Quality Platform Engineering to deliver fast, trustworthy safety signals across all platforms and devices, while building a strong team and culture.

Strong background in ML evaluation and productionML, cross-platform testing, and experience hiring technical teams are required.