At Epidemic Sound we are reinventing the music industry. Our carefully curated music catalogue, with over 30,000 tracks, is tailored for storytellers no matter what their story is. Countless customers around the world, from broadcasters, productions companies and YouTubers rely on our tracks to help them tell their stories. Epidemic Sound’s music is heard in hundreds of thousands of videos on online video platforms such as YouTube, Facebook, Twitch and Instagram. Our HQ is located in Stockholm with offices in NYC, LA, Hamburg, Amsterdam and Madrid. We are growing fast, we have lots of fun and we are transforming the music industry.
The growth of our business requires us to be excellent at building and maintaining relationships with our customers to inspire action and loyalty. To achieve this, we need to make our user experience next level, through intuitive machine learning and customer analytics.
We are now looking for an experienced Research Scientist (Machine Learning & Music Information Retrieval).
The position as a research scientist will report directly in to the CTO, in a fresh new team which functions as a de-centralised squad, delivering advanced analysis and machine learning to various departments throughout the company. The use cases range from classifying time-frequency domain representations and forecasting symbolic representations (including lyrics) – to building fantastic music recommenders to further personalize Epidemic Sound’s offering.
You will be working closely with backend machine learning engineers and data engineers in deploying fair, explainable and interpretable models. You will improve the personalization of the music browser by:
- Keeping up with (and contributing to) the latest state-of-the-art in music informatics and deep learning
- Developing classification systems through feature extraction on music to identify type & ‘feel’ of any given content
- Helping out with recommender systems (e.g. cold start) so that the music our users see first, is relevant to them based on their behaviours
- Contributing to the automation of previously manual tasks, by leveraging the classification systems you’ve contributed to building
- Consulting on appropriate implementation of algorithms in practice – and actively identifying new use cases that can help improve Epidemic Sound!
What are we looking for?
We’re looking for a team member with a “no task is too small” mindset – we are at the beginning of our Machine Learning journey – so we need someone who thinks building something from scratch sounds exciting.
It would be music to our ears if you are/have:
- PhD or MSc in a Quantitative or Computer Science based subject (Music Information Retrieval, Signal Processing, Sound & Music Computing)
- Solid grasp of musical terms like timbre, chroma, tempo, key signature, etc.
- Knowledge of MIR/audio analysis terms like acoustic fingerprinting, phase vocoder, short-time Fourier transform (STFT) and Mel-frequency cepstral coefficients (MFCCs)
- Extensive understanding of machine learning (neural networks, deep learning, classification, regression)
- Experience with machine learning in production and experience with MIR, signal processing and/or music theory
- Experience with: tensorflow, keras, pytorch, sciki-learn, scipy, numpy, pandas or similar
- Fluency in Python programming and a passion for production ready code
- Experience from Google Cloud
Curious about our music? Find our music on Spotify here → https://open.spotify.com/user/...
Do you want to be a part of our fantastic team? Please apply by clicking the link below!