Machine Learning Engineer Internship - Music Recommendation m/f/d

Company Description

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.  

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

 **Join Us**

Job Description

We are a leading company in the music streaming industry, with one of the largest catalogues on the market (over 120 million HiFi music tracks) and more than 9 million worldwide subscribers. To help access this vast amount of tracks, recommender systems are a key asset to retain and attract users. Suggesting relevant personalized songs, artists, albums, or playlists helps users actively explore the vast and mostly unknown musical landscape.

At Deezer, the recommendation team is in charge of building machine learning models and algorithms like the Flow to achieve such a goal. For this purpose, transformers have recently emerged as a competitive approach for sequence modeling and generation in various sequential recommendation problems.

Transformers were successfully trained and deployed to perform automatic playlist continuation and considered for other features. They revealed promising performances.

However, they can also exhibit some drawbacks like popularity biases. Consequently, they can impair accuracy and fairness in the recommendation algorithms.

The objective of this internship will be to investigate one of the critical aspects related to the training of Transformers for music recommendation at scale on Deezer: negative sampling.  The way we perform negative sampling during training is crucial. It is known to significantly impact the final performance of the Transformer, as well as its tendency to recommend popular tracks. 

The intern will be supervised by a Senior Data Scientist from the Recommendation team, and will also directly work with other engineers and research scientists from Deezer. They will provide scientific and technical guidance throughout the internship. For experiments, Deezer ensures access to internal data, cutting-edge technology, and appropriate calculus power. Several previous interns from our team have tested their algorithms in production, and/or have published results from their work as scientific articles.

Qualifications

• Master / PhD student with with a strong background in machine learning
• Good programming skills and knowledge of machine learning tools (such as scientific Python, PyTorch, Keras, etc)
• Creativity and autonomy
• Good data processing and analysis skills
• Knowledge and experience in recommender systems would be a plus
• Knowledge and experience in Transformer architectures would be a plus

Additional Information

Life @ Deezer Paris
- Start-up environment and philosophy
- Highly motivated and product-focused people ready to drive innovation
- In-house Deezer Sessions with your favorite artists, gig tickets
- Hackathons & meetups
- Friday drinks, summer and winter parties
- A stocked kitchen with free drinks and snacks
- Areas to relax and collaborate with beanbags, guitars and table football
- An ‘at home’ vibe, with great outdoor spaces
- Gym access at Deezer HQ with lunch-time yoga, pilates and boxing classes

If you feel like this is the right opportunity for you, press play!
We are an equal opportunity employer.