Music AI/ML QE Engineer

Apple Services sits at the heart of Apple's most beloved experiences, a place where the culture of curiosity, creativity, and relentless attention to detail that defines Apple is channelled into shipping features that reach hundreds of millions of people every day. We're looking for a Tools and Automation Engineer to partner with our Engineering and Stakeholder teams to build the automation, tooling, and testing infrastructure behind complex, customer-facing music recommendation systems (e.g., the dynamically personalised Home tab in Apple Music) under demanding timelines. Bonus points for experience supporting new product introductions. This is not a task-based job; you will be responsible for successful outcomes and delivery. Strong fundamentals in Python or Java are required. Experience with agentic testing, LLMs, or an understanding of stochastic automation is preferred but not essential, we care more about how you think than which specific tools you've used. You take ownership of what you build; you feel a personal stake in the reliability and quality of the systems you ship; you communicate scope and tradeoffs clearly; you value integrity; you thrive in ambiguity and bring order to it; you understand how systems actually work under the hood; you build strong relationships across engineering teams; you are constantly looking to improve your tools, your team, and yourself; and you ship automation that millions of customers benefit from, even if they never see it.

Description

The work will involve designing and implementing scalable automated test plans for music machine learning features. Some of the key responsibilities in this role will include:

Developing and maintaining automated test frameworks, scripts, and tools for functional, regression, integration, and performance testing

Invent, build and evaluate novel methods for automating quality analysis of large complex machine learning products

Investigate issues impacting and discovered by automated tests ensuring issues are accurately identified and resolved

Create systems that can perform loss pattern analysis on issues identified via automation

Collaborate cross functionally with various teams to achieve strategic quality goals

An excellent candidate will have passion for music and value great end-user experiences

Preferred Qualifications

Understanding of Machine Learning and LLMs

Data Visualisation

Stochastic Automation

Loss Pattern Analysis

Experience with databases and SQL

Minimum Qualifications

BSc in Computer Science or equivalent work experience

Experience developing in Python, Java or similar

Deep knowledge of QA test planning, bug lifecycle, engineering & release strategies

Excellent communication skills

Driven self-starter that can work independently and values collaboration