The Personalisation team strives to create a personalised user experience on TIDAL by creating algorithmic playlists, tailoring users homepage recommendations and other ML powered features. Our team is growing and we are looking for ML Engineers who are excited about solving interesting music recommendation problems as part of a smaller team.
Our ML Engineers work in close collaboration with Product, Data Analysts, Design and Product from across TIDAL. You will report to the Personalisation Engineering Manager. In the team we use a wide range of models including simple heuristics, embeddings and deep learning to build our recommender systems. We’re open to in-office, hybrid or fully remote for this role - you choose whatever works the best for you.
You Will:
Develop new recommender systems that powers TIDAL’s homepage and algorithmic playlists
Build production systems that personalize our listener’s experience on the platform
Be a technical leader and establish quality practices that stick, make broader design decisions and set an example for others to follow
Collaborate with a cross functional team of designers, product managers and software engineers to build new technologies and features
Design experiments, test them on production users, analyze and repeat
You have:
8+ years building and operating quality software
5+ years of experience with recommender systems, ranking systems, or similar
Led the development of complex models trained on large datasets powering customer facing features
Strong software engineering skills
Strong communication skills and customer empathy
Experience with PyTorch, PySpark, Databricks and AWS is a plus
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