AIML Quality Engineering Manager, Responsible AI and Safety

What you'll do

• Hire, grow, and build the culture of a team spanning test engineering, applied ML, and platform-specific expertise.
• Translate pipeline health, coverage, and findings into risk and product terms for non-technical stakeholders.
• Reprioritize feature clusters, platforms, and hardware form factors based on risk, launch timing, and coverage gaps.
• Drive investment in test pipeline efficiency to improve turnaround time, infrastructure cost, and flakiness.
• Extend safety testing coverage to every platform and device category Apple ships by partnering with platform teams.
• Upstream trusted datasets for product-critical safety cases to provide component teams with reliable ground truth.
• Champion shift-left safety testing to catch issues at the component level before end-to-end evaluation.
• Ensure pre-merge results reliably predict end-to-end outcomes by aligning signals with Product Evaluations & Research metrics.

What we're looking for

• 5+ years of technical team management or leadership experience.
• Experience with ML evaluation, production ML systems, or test/CI infrastructure at scale.
• Strong engineering skills and experience writing production-quality code in Python or similar.
• Experience working across multiple platforms or hardware form factors, or the ability to ramp quickly across unfamiliar platforms.
• Experience working with human-labeled or crowd-sourced evaluation data, including reasoning about label noise and inter-rater agreement.
• Experience working on Responsible AI, AI safety, or trust & safety-adjacent engineering (preferred).
• Experience with generative model evaluation and common failure modes (preferred).
• MS or PhD in Computer Science, Machine Learning, Statistics, or related field, or equivalent experience (preferred).