Deezer - Research internship - music recommendation

Deadline: As soon as possible

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Location(s)

  • France
24 Rue de Calais, 75009 Paris

Overview

Ready for an electrifying journey? Apply now and do your part in bringing extraordinary music experiences to people’s lives!

Details

LIVE THE MUSIC WITH US 

From a pioneer tech start-up created in 2007, Deezer has become one of the first French unicorns and the second largest independent music streaming platform in the world. At sixteen years old, we’re only just coming of age. Now listed on #EuroNext, Deezer is a rapidly-growing, cutting-edge player in the music streaming market. If you want an environment where you can make your voice heard and be at the forefront of music and tech, look no further!

We believe music is all about embracing the things that make us different. Deezer is a vibrant community that celebrates uniqueness, diversity and individuality, and thrives on collaboration.

Our international and passionate teams pride themselves on being at the forefront of the music experience, going beyond streaming and helping the world to Live the Music. We’re constantly evolving alongside our customers, partners, artists and employees — striving to make Deezer the most personal and innovative streaming service in the world.  

Job Description

Current recommendation systems rely heavily on latent collaborative filtering (CF) models, which analyze usage data to generate low-dimensional embeddings for users and tracks. However, while effective, CF-based models have inherent limitations such as limited coverage of the catalog and slow integration of new releases in the recommendation engine. This internship will address these challenges by exploring multimodal machine learning approaches. By integrating diverse data sources - such as CF, text and audio embeddings - these methods aim to create a comprehensive multimodal embedding space for tracks, leveraged for downstream recommendation / retrieval tasks.

  • Conduct an in-depth review of state-of-the-art multimodal methods.

  • Design and implement multimodal models for recommendation and/or retrieval.

  • Apply these models to real-world Deezer datasets and benchmark their performance.

  • Optionally, contribute to publications and / or conduct A/B testing of selected methods in a production environment.

Opportunity is About


Eligibility

Candidates should be from:


Description of Ideal Candidate

Qualifications

  • Master / PhD student with a background in Computer Science / Applied Mathematics / Statistics.

  • Strong knowledge of music analysis, natural language processing, applied machine learning and data mining

  • Good programming skills for data processing and experimentation (preferred python)

  • Creativity and autonomy


Dates

Deadline: As soon as possible


Cost/funding for participants

Additional Information

At Deezer, you can be your true self as we believe that #everyvoicematters. We strive to build an inclusive culture and foster a diverse environment. Because we care and want to ensure each employee feels welcome and safe at work, we continuously focus on fighting biases and helping diverse teams work well together through multiple learning opportunities, e-learnings and workshops right from the onboarding :

  • Regular Diversity & Inclusion internal and external talks
  • Dedicated employee work streams on Gender equity, Ethnicity & Culture, Disability and LGBTQ+
  • Multiple e-learnings and mandatory training sessions for all managers
  • English and French courses for all, so that everyone can connect and feel included

Beyond benefits like transportation, we offer you extra perks like:

  • A Deezer premium family account for free
  • Access to gym classes
  • Deezer parties several times a year and drinks every thursday
  • Allowance for sports, travelling and culture …
  • Meal vouchers
  • Great offices always located in dynamic and attractive districts, whether in Paris, London, Berlin or Sao Paulo!
  • Hybrid remote work policy
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