Director, Evaluation and Quality Assurance, Services Special Projects - Jobs - Careers at Apple
- Design metrics and automated grading systems ("autograders") that scale to large, frequently changing datasets, utilizing those alongside human evaluation, and determining where the line between those should sit.
- Wiring evaluation results into release processes as explicit quality gates, not just after-the-fact reporting.
- Catching and preventing quality regressions across an entire product surface — from user-facing correctness to backend transaction integrity.
- Partnering with engineering and applied ML teams to define what "quality" and "done" mean before a product's own definitions of those things have settled.
- Navigating ambiguity and building structure — process, tooling, org design — in an environment where none of it exists yet.
- Making judgment calls under uncertainty about where to invest limited evaluation resources for maximum risk reduction.
- 12+ years of experience in data science, machine learning evaluation, quality assurance, or test engineering roles in a technical product environment, including experience building and leading multi-level QA or evaluation organizations through managers.
- Demonstrated experience building an evaluation or QA function from the ground up — defining metrics, process, tooling, and organizational structure where none previously existed.
- Extensive experience utilizing LLM-based autograders and rubrics, including rubric design, evaluation set development, validation, calibration, and human-model alignment, and using them to proactively drive product and model improvements.
- Deep experience in traditional human evaluation methodology, logging, and A/B testing for consumer-facing products at scale.
- Experience evaluating conversational AI, recommendation, ranking, or search systems, and — ideally — agentic or tool-use systems that take real-world actions, not just generate responses.
- BS in Computer Science, Engineering, or a related technical field, or equivalent experience.
- Experience with quality assurance for third-party API integrations.
- Experience with logging infrastructure and instrumentation for AI product quality measurement.
- Exceptional written and verbal communication skills, with a track record of presenting quality status, risk, and trade-offs clearly to, and influencing decisions among, senior executive leadership.
- 15+ years of experience in data science, machine learning evaluation, quality assurance, or test engineering roles in a technical product environment, including experience building and leading multi-level QA or evaluation organizations through managers.
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Required Languages
🇬🇧 English