Requirements

• Experience building production applications on top of LLMs, including tool use, structured output or agentic designs.
• Hands-on experience with prompt engineering and systematic model evaluation, such as writing rubrics or graders and measuring precision and false-positive rates.
• Strong programming skills in Swift / Python, and experience building backends for ML applications.
• Ability to improve model behavior iteratively, based on measured results.

Nice to Haves

• Hands-on experience fine-tuning or training models.
• Experience with computer vision or object detection, such as detecting elements in screenshots or documents.
• Experience with open-weights models and local inference.
• Experience with multi-agent systems.
• Familiarity with LLM serving infrastructure, such as model gateways, retries and cost-aware model selection.
• Experience building feedback loops that turn model failures into improved prompts, classifiers or training data.
• Familiarity with software test automation concepts, such as test execution, pass/fail grading and CI/CD.
• Experience in software localization or internationalization.
• Experience mentoring other engineers.

What You'll Be Doing

• Designing LLM-based solutions and evaluating their accuracy to improve AI-powered quality systems.
• Owning the model-facing side of quality systems to make them reliable, efficient, and trustworthy.
• Working alongside automation, quality, and localization engineers as well as international quality engineers, translators, and project managers.
• Helping Apple ship better software to users worldwide.