We are seeking a Senior Machine Learning Engineer to join the Ad Engagement squad. Ad Engagement focuses on using machine learning to accurately predict how Spotify listeners will react to ads, helping advertisers minimize their costs while delivering a more relevant and enjoyable ad experience for listeners. Our core innovations include Multi-Task Learning models (MTL), and we are expanding into scalable sequence modeling with complex transformer architectures. Recently, we presented a paper about this in KDD Toronto and you can check out the latest details in the blog post
here.
We are also seeking a Senior Machine Learning Engineer to join the Supply Personalization squad. Supply Personalization focuses on optimizing the volume, timing, and types of ad loads a user receives. By leveraging data, machine learning, causal inference, and large scale online experimentation, we aim to uncover and learn the most effective strategies for enhancing user experiences and driving business outcomes.
We are looking for someone with strong expertise in data analysis, online experimentation techniques, and large-scale ML and engineering systems; someone who is motivated by user and business problems as much as they are by technical problems, and who thrives under ambiguity, experimentation, and iteration. You will work directly on an array of product features that drive the optimal user experience for our ads. You will collaborate with our cross-functional teams to ideate, develop, and own complex technical solutions on our ad services technology platforms. As someone who shares our passion for building innovative ad experiences, you'll have a direct impact on how the world uses Spotify.