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

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Universal Music Group

2mo ago

  • Internship
    Full-time
    Summer Internship
  • Data
    IT & Cybersecurity
  • London
  • Quick Apply

AI generated summary

  • You should have experience in audio ML, strong Python skills, knowledge of Deep Learning frameworks, Linux familiarity, and a passion for music. Publications and cloud experience are a plus.
  • You will design and build AI/ML and audio algorithms, explore research in AI/MIR, collaborate with team members, and communicate findings to diverse audiences.

Requirements

  • 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
  • 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

Responsibilities

  • 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

FAQs

What is the duration of the internship?

The internship lasts for 4 months, from June to September 2025.

What team will I be working with as an intern?

You will be working with the Music and Audio Machine Learning Lab (MAML) team.

What are the main responsibilities of this internship?

You will design and build AI/Machine Learning and audio algorithms, explore cutting-edge research in AI/ML/MIR/Audio, collaborate with team members and stakeholders, and communicate findings to various audiences.

Is a background in Music Information Retrieval necessary for this role?

Yes, a background in Music Information Retrieval, Machine Learning, or Audio Signal Processing is necessary.

What programming languages and tools should I be familiar with?

You should have a thorough knowledge of Python and scientific libraries such as Numpy, Scipy, and sklearn, as well as experience with Deep Learning frameworks like Pytorch and TensorFlow.

Are there any preferred qualifications for candidates?

Yes, desirable qualifications include a track record of publications in relevant conferences, familiarity with Generative AI, and experience with cloud computing environments and containerized software development.

Will there be opportunities for collaboration in the internship?

Yes, you will have the chance to collaborate with team members and stakeholders throughout the internship.

Is there a focus on diversity and inclusivity in the hiring process?

Yes, Universal Music is committed to diversity and inclusivity, ensuring that no applicant or employee receives less favorable treatment based on various factors including gender, race, disability, and neurocognitive variations.

Can I adjust my internship focus based on my interests?

Yes, the focus of the internship can be adapted to the candidate’s interests and background.

What qualities are you looking for in a candidate?

We are looking for candidates who are curious, self-motivated, proactive, and possess good communication skills.

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Universal Music Group

We are Universal Music Group, the world’s leading music company.

Entertainment & Media
Industry
5001-10,000
Employees
1934
Founded Year

Mission & Purpose

Universal Music Group (UMG) is the world leader in music-based entertainment, with a broad array of businesses engaged in recorded music, music publishing, merchandising and audiovisual content in more than 60 countries. Featuring the most comprehensive catalog of recordings and songs across every musical genre, UMG identifies and develops artists and produces and distributes the most critically acclaimed and commercially successful music in the world. Committed to artistry, innovation and entrepreneurship, UMG fosters the development of services, platforms and business models in order to broaden artistic and commercial opportunities for our artists and create new experiences for fans. Universal Music Group's labels include A&M Records, Astralwerks, Blue Note Records, Capitol Christian Music Group, Capitol Records, Capitol Records Nashville, Caroline, Decca, Def Jam Recordings, Deutsche Grammophon, Disa, Emarcy, EMI Records Nashville, Fonovisa, Geffen Records, Harvest, Interscope Records, Island Records, Machete Music, MCA Nashville, Mercury Nashville, Mercury Records, Motown Records, Polydor Records, Republic Records, Universal Music Latino, Verve Label Group, Virgin Records, Virgin EMI Records, as well as a multitude of record labels owned or distributed by its record company subsidiaries around the world. UMG's catalog is marketed through two distinct divisions, Universal Music Enterprises (in the U.S.) and Universal Strategic Marketing (outside the U.S.). UMG also includes Universal Music Publishing Group, one of the industry's premier music publishing operations worldwide and Bravado, the leading provider of consumer, lifestyle and branding services to recording artists and entertainment brands around the world. Universal Music Group is a Vivendi company.

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