Senior Audio Intelligence Triage and Integration Engineer, Watch Software

Do you want to help deliver the next amazing Apple product? The Apple Watch software team is seeking an Audio Intelligence Triage and Integration Engineer to investigate complex issues in our intelligent audio features, integrate changes across teams, and build AI tools and automation that scale the team’s impact. You will work across the full software stack and help engineering triage complex problems.

In this role, you will triage complex issues in our audio intelligence features, which combine sound and speech recognition, on-device and cloud-based language models, and secure system software. You will reproduce issues, analyze logs and diagnostics, find root causes and regression points, and route each issue to the right owner with a clear priority and actionable next steps. You will integrate changes and coordinate testing with QA teams, and build AI-assisted tools and agentic workflows that make triage faster and more accurate. We are looking for a deeply technical, curious engineer who enjoys hard debugging problems and wants to help shape how Apple builds reliable intelligent features.

Minimum Qualifications

• Bachelor’s degree in Computer Science or a related field, or equivalent professional experience
• 5+ years of experience in software development, quality, or reliability engineering
• Strong debugging skills with macOS, iOS, or other UNIX-based systems, and an understanding of OS fundamentals such as processes, memory, and concurrency
• Proficiency in Python and shell scripting, and the ability to understand and debug Swift, Objective-C, or C
• Hands-on experience building tools or workflows with LLMs, including agents, skills, or Model Context Protocol (MCP)
• Understanding of how ML models are evaluated and deployed, and how they fail
• Experience with bug tracking, source control (preferably git), and continuous integration systems
• Excellent communication skills and the ability to work across teams to drive issues to resolution

Preferred Qualifications

• Experience with speech recognition, audio processing, natural language processing, or LLM-based features
• Experience with on-device ML, including Core ML
• Experience with Xcode, Instruments, and performance or power profiling
• Experience with retrieval-augmented generation (RAG) or knowledge systems that give LLM tools context
• Experience building tools adopted by engineering teams beyond your own
• Experience with data analytics and understanding large data sets