{"id":1098453,"url":"https://alion.io/job/spotify-research-scientist-personalization-2","title":"Research Scientist - Personalization","company":{"id":57,"name":"Spotify","domain":"spotify.com","url":"https://alion.io/company/spotify","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Lever","truth_index":{"grade":"B","score":83,"open_postings":13,"ghost_share":0,"stale_share":0.615,"repost_share":0.077,"time_to_fill_p50_days":50,"computed_at":"2026-11-10T06:52:35Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["New York, United States"],"countries":["US"],"hiring_countries":["US"],"hiring_countries_total":1,"salary":null,"salary_estimate":{"min_usd":156000,"max_usd":347000,"period":"year","method":"role_country_seniority_unknown","sample_n":4425},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Machine Learning","optional":false},{"name":"Post-training","optional":false},{"name":"Reinforcement Learning","optional":false}],"status":"live","first_seen_at":"2026-09-21T17:37:41Z","employer_posted_date":"2026-09-21","last_verified_at":"2026-11-10T09:26:48Z","board_verified":true,"closed_at":null,"days_open":49,"trust":{"level":"ok","repost_count":1,"flags":[],"days_open":49},"description":"The Personalization team makes deciding what to play next easier and more enjoyable for every listener. From Blend to Discover Weekly, we’re behind some of Spotify’s most-loved features. We built them by understanding the world of music and podcasts better than anyone else. Join us and you’ll keep millions of users listening by making great recommendations to each and every one of them.Spotify’s\nPersonalization organization builds the technology that helps millions of listeners discover what they love. Within this space, our research team focuses on advancing the state of the art in machine learning and AI to shape the future of personalization. We explore new approaches, challenge existing assumptions, and contribute to the broader research community while influencing long-term product direction.\nWhat You'll Do\nConduct original research in machine learning and AI, with a focus on large-scale foundation models, generative AI, and post-training methods, including reinforcement learning.\nDevelop novel methodologies, models, and evaluation frameworks to advance personalization systems.\nDesign and execute rigorous experiments to explore new ideas and validate research hypotheses.\nContribute to the scientific community through publications, talks, and conference participation.\nCollaborate with cross-functional partners to translate research insights into long-term product opportunities.\nHelp define and evolve a forward-looking research agenda aligned with Spotify’s personalization strategy.\nMentor others and contribute to a strong, curious, and collaborative research culture.\nWho You Are\nYou have a Master’s or PhD in machine learning, AI, or a related field, or equivalent research experience.\nYou have demonstrated expertise in machine learning and artificial intelligence through peer-reviewed publications at conferences such as NeurIPS, ICLR, ICML, KDD, or RecSys.\nYou have deep knowledge of machine learning, with hands-on experience in areas such as post-training and reinforcement learning for large models, reward design, large-scale distributed training, or evaluation of model behavior.\nYou are experienced in designing experiments and working with real-world datasets to validate research ideas.\nYou care about advancing understanding of user behavior and improving experiences across music and talk content.\nYou bring curiosity, creativity, and a thoughtful approach to solving complex, open-ended problems.\nYou value collaboration and actively seek diverse perspectives in your work.\nWhere You'll Be\nThis role is based in New York City.\nWe offer you the flexibility to work where you work best! 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