Our team builds frameworks, services, and tools that accelerate feature development for
engineering teams. We bring a quality-first perspective to end-to-end solutions: dependable
systems that our engineering teams can trust day after day.
In this role, you'll apply your quality engineering expertise to the evaluation workflows that
measure the reliability and accuracy of generative AI systems. You'll integrate our evaluation
platform with enterprise services, build the data pipelines that capture and store evaluation
results, and establish validation frameworks that maintain Apple's standards for quality.
Minimum Qualifications
Bachelor's degree in Computer Science, Computer Engineering, or a related field, or 3 years
of equivalent work experience.
3+ years of experience building and operating production software in Python.
Experience debugging distributed systems or data pipelines in production, using logs, metrics,
and task state to find root causes.
Experience designing input validation and configuration contracts for systems where late
failures are costly.
Proven, hands-on use of agentic AI coding tools in day-to-day software development,
including judging where they are effective and where their output needs human verification.
Strong communication skills.
Preferred Qualifications
Experience with model evaluation frameworks or ML infrastructure.
Experience working directly with partner teams or internal customers to define and ship
features.
Experience measuring the domain gap between synthetic and real data, including visual
statistics and non-visual properties such as metadata and label distributions.
Experience with generative image, video, or large language model APIs, including structured
output.
Familiarity with image and video file formats and metadata standards.
Experience with batch compute platforms or job schedulers.