The AIML team in Apple Services Engineering is building the future of how millions of users discover, explore, and enjoy music across Apple Music, Siri, Spotlight.
Our mission is to help every user find and experience the content they love—effortlessly and personally—by harnessing the potential of Machine Learning, Natural Language Understanding, and Generative AI.
As part of the Music Search team, you’ll work at the intersection of machine learning, language understanding, and generative AI, crafting next-generation search and recommendation experiences. Your work will shape how users connect with the songs, artists, and playlists they love
Description
As Machine Engineer on the Music Search team within Apple Services Engineering (AIML), you will help shape the future of how millions of users discover and experience music across Apple platforms. You’ll design and deploy models that combine machine learning, natural language understanding, and generative AI to deliver more intuitive and personalized search experiences.
You will build systems that understand user intent, rank results intelligently, and bring the magic of LLMs and transformer-based models into real-world applications. This is a hands-on role where your work will directly impact how users interact with Apple Music app, Siri, Spotlight, and other experiences across the Apple ecosystem.
Minimum Qualifications
2+ years of experience in machine learning, natural language processing, information retrieval, or LLM-based systems.
Strong programming skills in Python or C++, with experience building scalable ML systems.
Deep understanding of transformer architectures, embeddings, and retrieval or ranking models.
Experience applying or fine-tuning Large Language Models (LLMs) for understanding and generation tasks.
Familiarity with prompt design, contextual retrieval, or RAG-style architectures.
Proven ability to translate product goals into technical solutions and deliver measurable improvements in user experience.
Excellent communication, collaboration, and analytical problem-solving skills.
Preferred Qualifications
Experience with music, media, or recommendation systems.
Background in semantic retrieval, vector databases, or hybrid search architectures.
Hands-on experience with PyT orch, JAX, or TensorFlow for model training and deployment.
Exposure to evaluation and safety frameworks for LLM-based systems.
Understanding of reinforcement learning from human feedback (RLHF) or preference modeling.
Passion for crafting intelligent, human-centered experiences that enhance music discovery.
Responsibilities
In this role, you will:
Build and deploy LLM-powered and ML-driven models to improve search relevance, personalization, and user intent understanding for music discovery.
Design retrieval and ranking systems that combine semantics, user context, and catalog metadata.
Collaborate with cross-functional teams across engineering, data science, and design to define the next frontier of intelligent music search.
Analyze large-scale data and model performance to identify new opportunities for improving search quality.
Ensure your systems meet Apple’s standards for privacy, efficiency, and delightful user experience.
Eeo Content
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant.
