Location
London

Hours
Full Time

Salary
Negotiable

About the Role
Join the Computational Music Technologies team, where we build the audio intelligence behind some of Apple’s most distinctive listening experiences. Our team has shipped AutoMix, intelligent DJ-style transitions between tracks, and the Music Understanding Framework, an on-device audio feature extraction system. We are now developing the next generation of generative audio technology, including foundational models that will support a variety of new experiences for music lovers and creators across Apple.

Music is our passion, and so is conducting rigorous research: we emphasize thorough evaluation, artist and listener trust, and a bias toward shipping impactful products. Our team collaborates closely with research and engineering partners across Apple and has access to large GPU clusters to enable ambitious foundational work.

As a Machine Learning Researcher, you will conduct research in generative audio using diffusion or flow-matching models, focusing on one or more of the following areas: voice generation including vocal and speech synthesis alongside related audio and signal processing techniques; post-training and alignment methods to improve output quality, controllability, and alignment with human preferences; and realtime generation, developing architectures and distillation methods to reduce generation latency for live use, including few-step and streaming approaches.

Additionally, you will help build the foundational components that support this work, such as evaluation methodologies, benchmarking against state-of-the-art models, and attribution questions. You will run large-scale experiments on Apple’s infrastructure, collaborate closely with engineering, product, and design teams to translate research into real listening experiences, and stay connected with the broader research community.

Experience
- PhD in computer science, statistics, applied mathematics, or a related field
- Peer-reviewed publications at top venues such as ICASSP, ISMIR, Interspeech, NeurIPS, ICLR, ICML, or related conferences
- Expertise in generative modelling, machine learning, music information retrieval, or speech and audio processing
- Industry experience coding in Python and PyTorch or JAX

About you
- Excellent communication and presentation skills
- Deep expertise in at least one of the following areas: audio generation and editing, post-training of diffusion models, voice synthesis
- Experience integrating machine learning models into consumer-facing applications
- Passion for music and audio technology

Qualifications
PhD degree in a relevant field and demonstrated research excellence through publications and practical experience.