Scientist with a machine learning background to help us improve personalization experiences by integrating state-of-the-art generative AI technologies into our recommender systems. You will join a team of machine learning researchers whose focus is on innovating the Spotify experience through researching and developing ML technologies … at conferences or journals such as NeurIPS, ICML, ICLR, KDD or related. A solid understanding of machine learning and past research experience on recommender systems. Solid hands-on skills in implementing advanced ML algorithms, as well as sourcing, cleaning, analyzing and modeling of large-scale real data. You More ❯
developing standardized, efficient ML solutions in critical domains like parameter-efficient tuning, multimodal modeling, media generation, LLMs, and recommender systems. The ML, Systems, & Cloud AI (MSCA) organization at Google designs, implements, and manages the hardware, software, machine learning, and systems infrastructure for all Google services (Search More ❯
developing standardized, efficient ML solutions in critical domains like parameter-efficient tuning, multimodal modeling, media generation, LLMs, and recommender systems. The ML, Systems, & Cloud AI (MSCA) organization at Google designs, implements, and manages the hardware, software, machine learning, and systems infrastructure for all Google services (Search More ❯
engagement and retention through intelligent, personalised notifications. Leveraging machine learning models and tooling you will oversee the development and implementation of a sophisticated recommendersystem determining which notifications to send to which users, thereby significantly boosting app retention. What you'll do Lead Notification Strategy: Drive the strategy … execution to ensure timely delivery of initiatives, overcoming obstacles and ensuring team alignment. Outcome 1: Increase user retention Ship an ML-powered notification recommender that delivers personalised, timely, insightful messages. Work cross functionally with DS and Engineering to ensure the recommender can scale and have an More ❯
