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 teams 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.

Investigate complex issues across the software stack from the user interface to on-device ML and system software and identify root causes and regression pointsnAnalyze logs crash reports and diagnostics identify trends and recurring issues and work with owning teams to drive them to resolutionnIntegrate software changes and provide patches to engineering and QA teams for evaluationnDesign build and deploy AI-assisted triage tools and agentic workflows using LLMs skills and MCPnBuild and maintain shared knowledge that gives engineers and AI tools the context they need to triage accuratelynMeasure the accuracy and impact of AI tools and improve them based on the results

Bachelors degree in Computer Science or a related field or equivalent professional experiencen5 years of experience in software development quality or reliability engineeringnStrong debugging skills with macOS iOS or other UNIX-based systems and an understanding of OS fundamentals such as processes memory and concurrencynProficiency in Python and shell scripting and the ability to understand and debug Swift Objective-C or CnHands-on experience building tools or workflows with LLMs including agents skills or Model Context Protocol (MCP)nUnderstanding of how ML models are evaluated and deployed and how they failnExperience with bug tracking source control (preferably git) and continuous integration systemsnExcellent communication skills and the ability to work across teams to drive issues to resolution

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