ABOUT MUSIXMATCH:
Musixmatch is the leading music metadata company, featuring the world's largest lyrics catalog and +70M user contributors. Musixmatch is the trusted global partner of companies like Spotify, Apple, Amazon Music, Meta, Google, MTV, Shazam, Vevo and has a partnership with +100,000 music publishers including Sony/ Music Publishing, Universal Music Publishing, Warner/Chappell, Kobalt, BMG Rights, and the Harry Fox Agency.
We are a bunch of creatives who care about our work and what we do. We believe that participation and collaboration are key to getting things done well. We are looking for tech-savvy people who are eager to learn in a fast-paced environment, who have an international outlook on life, and who love taking on new challenges.
Position:
We are looking for an experienced Data Scientist, who is passionate about writing clean code and technical papers, to join our AI Team.
As part of our team, you will work in a cross-team environment, contributing to research that can be applied to Musixmatch products by adapting creative approaches.
What will you do:
You will work in the field of Natural Language Understanding and Prompt Engineering, by making use of all recent advances in LLMs, as well as on Music and Audio Processing and Image/Video tasks.
You will develop SDKs and frameworks to deploy our AI capabilities on servers, desktop and mobile devices.
You will prototype innovative and state-of-the-art AI solutions for inferencing and training to be integrated into our infrastructure.
You will be asked to solve complex problems through the design of new AI solutions by adopting creative approaches and by making use of Musixmatch's large datasets.
You will work in a cross-team environment, effectively communicating with Product Managers and Software Engineers in order to meet product requirements, optimize and scale your systems effectively.
You will be responsible for creating clear, concise, and up-to-date technical documentation that effectively communicates the technical aspects of your projects. This includes ensuring the documentation is well-structured, accurate, and easy to understand, enabling both technical and non-technical stakeholders to fully comprehend the project's details and implementation.
You will provide support and mentorship to other junior engineers when needed, sharing your knowledge and expertise with the Team.
Requirements:
You have a M.Sc. or PhD in one of these fields: Engineering and Computer Science, Mathematics, Machine Learning, Data Mining, Information Retrieval, Natural Language Processing, Audio Signal Processing, Computational Advertising, Deep Learning, Computer Vision or related fields.
You have at least 2 years experience in Python programming.
You are familiar with one or more of these Machine Learning frameworks: Pytorch, TensorFlow, Keras.
You have a good knowledge of popular Data Science/Machine Learning library tools such as: NumPy, SciPy, scikit-learn.
You have experience working with Search Engines for indexing metadata and embeddings.
Demonstrated ability of working in a cross-team environment.
Fluency in English.
Nice to have:
Experience programming in TypeScript/Node.js.
Experience programming in C++.
Experience with MLOps with popular cloud computing platforms such as: Amazon Web Services, Microsoft Azure, Google Cloud.
Experience with vector-based Search Engines and Databases.
Experience with traditional documental Databases and Graph Databases.
Experience in working with LLMs (fine-tuning, quantization) and Prompt Engineering.
Experience in the field of Generative AI applied to Audio, Image and Video.
WHAT WE OFFER:
Flexible schedule Generous training budget Top class tech and equipment Company-wide retreat once per year Welfare plan
DISCLAIMER:
**Due to the significant amount of applications we receive, unfortunately, it is not possible to answer every applicant. If you have not received a response from us, please be patient. We assure you that we will contact you should you be selected to move forward in the recruitment process. We would therefore like to thank all applicants for their interest and time.**
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