Audio & Machine Learning Summer Intern (4 Months - June - Sept 25)

Umusic is hiring an Audio & Machine Learning Summer Intern (4 Months - June - Sept 25) in Kings Cross, London. Posted March 6, 2025. Checked against the employer's posting on November 12, 2026.

Music is Universal It’s the passionate and dedicated team at Universal Music who help make us the world’s leading music company. From A&R to finance, legal to digital, sales to marketing, Universal Music is the place to grow and develop your career within a truly commercial and innovative business that leads in everything it does.

Everyone is welcome to apply for our roles, and we are determined to ensure that no applicant or employee receives less favourable treatment because of gender, race, disability, sexual orientation, religion, belief, age, marital status, background, pregnancy, or caring responsibilities.

We also recognise the importance of diversity of thought within our teams and are fully committed to embracing the talents of people with autism, dyslexia, ADHD, and other forms of neurocognitive variation.

We will always seek to make appropriate adjustments to recruitment, workplaces, and work processes to be fully inclusive to people with different needs and working styles.

If you need us to make any reasonable adjustments for you from application onwards, including alternatives to the online form or to disclose a neurocognitive condition, please email UniversalMusicCareers@umusic.

com. The A Side: A Day in The Life This role sits within the Music and Audio Machine Learning Lab (MAML). The MAML’s mission is to support and empower UMG business units and partners with advanced technologies such as AI, Machine Learning and Digital Signal Processing.

The MAML covers the full research & development lifecycle, from explorative research to prototypes to industrial scale products. It typically undertakes projects with applications such as, but not limited to, analysis and description of recordings, creative tools, search, recommendation, playlisting, content integrity etc.

The focus of the internship can be adapted to the candidate’s interest and background, but we have a particular interest in individuals with knowledge and experience of generative modelling.

We are an innovative and dynamic team. We are curious, passionate and always looking to push the state of the art in AI for music. The future in this space is terribly exciting and we want to take part in shaping it.

Our team member support each other every day in the pursuit of this goal. As an Audio & Machine Learning Summer Intern, you will: • Design and build state-of-the-art AI / Machine Learning and Audio algorithms • Explore cutting-edge research in AI/ML/MIR/Audio and new application avenues for UMG • Collaborate with the team and stakeholders • Communicate results and findings to audiences of all levels of expertise.

• Be part of an innovative and dynamic team If you are excited at the idea of working on state-of-the-art music & audio machine learning at industry scale and make an impact, we want to hear from you!

The B Side: Skills & Experience Person Specification Necessary • Background in Music Information Retrieval / Machine Learning / Audio Signal Processing • Up to date knowledge of AI / Machine Learning / Deep Learning state of the art • Hands on experience in music ML tasks such as music classification, music generation, source separation, representation learning, multi-modal deep learning or related tasks • Strong software engineering background • Thorough knowledge of Python and usual scientific libraries e.

g. Numpy, Scipy, sklearn etc. • Comprehensive knowledge and experience of Deep Learning and its usual frameworks (Pytorch, Tensorflow) • Familiarity with Linux environments • Ability to write good, well documented, and reusable code • Good communication skills • Curious, self-motivated, and proactive Desirable • Track record of publication(s) in relevant conferences or journals (e.

g. ISMIR, ICASSP, ICML, ICLR etc) • Familiarity/experience with Generative AI (e.g. latent diffusion, auto-regressive transformers etc) • Familiarity/experience with cloud computing environments (e.

g. AWS, Google Cloud Platform) • Experience with containerised software development (Docker) • Passion for music and/or deep musical understanding Just So You Know… The company presents this job description as a guide to the major areas and duties for which the jobholder is accountable.

However, the business operates in an environment that demands change and the jobholder's specific responsibilities and activities will vary and develop.

Therefore, the job description should be seen as indicative and not as a permanent, definitive, and exhaustive statement.