6 hours ago
Beijing, ChinaSenior
Responsibilities
- Champion product quality for Siri features and intelligent services across the full development lifecycle.
- Architect and implement test automation frameworks for client-side applications, backend services, and end-to-end integration flows.
- Build LLM-driven QA and evaluation pipelines, including automated test generation, offline model evaluation, self-healing end-to-end automation, online monitoring, and A/B experimentation quality assessment.
- Define model-quality metrics and dashboards; collect, categorize, and analyze bad cases including hallucinations, tool-invocation errors, retrieval failures, and prompt deficiencies.
- Design evaluation schemes, benchmark datasets, adversarial samples, negative samples, and edge cases for conversational AI, RAG, tool-use, agents, and multimodal scenarios.
- Develop lightweight AI-driven developer productivity tools, including agentic workflows and LLM-assisted code or test generation.
- Evaluate content safety, compliance, privacy, bias, harmful-content generation, and other responsible AI risks.
- Collaborate with geographically distributed, cross-functional teams to investigate issues and drive closed-loop quality improvements.
Requirements
- Bachelor’s or master’s degree in Computer Science, Computer Engineering, or equivalent practical experience.
- Strong proficiency in at least one of Python, Swift, Java, or Go.
- Solid foundations in data structures, databases, SQL, and Unix/Linux/macOS operating systems.
- Hands-on experience architecting and implementing test automation frameworks for client applications, backend services, and end-to-end integration flows.
- Experience with CI/CD pipelines, containerization, and modern cloud or distributed infrastructure.
- Understanding of Generative AI and LLM concepts, with the ability to build tools, scripts, or workflows using model APIs.
- Strong analytical, logical, debugging, communication, and interpersonal skills.
- Professional working proficiency in written and spoken English and Mandarin.
- Experience establishing LLM-based lifecycle QA systems and automated evaluation pipelines.
- Experience defining model-quality metrics and dashboards and analyzing categorized model failures.
- Experience designing evaluation schemes, benchmark datasets, adversarial or negative samples, and edge cases across conversational AI, RAG, tool-use, agents, and multimodal scenarios.
- Experience developing AI-driven developer productivity tooling.
- Experience with content safety, compliance, privacy, and responsible AI risk evaluation.
- Experience testing on Apple platforms including iOS, iPadOS, macOS, and watchOS.
- Fluency or proficiency in Cantonese is a strong plus.
About Apple
Apple designs and sells consumer electronics, software, and services for consumers and professionals worldwide, including iPhone, Mac, iPad, Apple Watch, and AirPods, plus platforms like iOS/macOS and services such as the App Store, iCloud, Music, and TV+. Its business combines device sales with services and subscriptions and in-house silicon design. Founded in 1976, Apple is headquartered in Cupertino, California, and trades on NASDAQ as AAPL.