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Siri Quality Engineer

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Siri Quality Engineer in Others

  • Beijing, China

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.

Apple

We’re a diverse collective of thinkers and doers, continually reimagining what’s possible to help us all do what we love in new ways. And the same innovation that goes into our products also applies to our practices — strengthening our commitment to leave the world better than we found it. This i...

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