{"id":1999951,"url":"https://alion.io/job/spotify-senior-machine-learning-engineering-manager","title":"Senior Machine Learning Engineering Manager - Content Platform","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":81,"open_postings":14,"ghost_share":0,"stale_share":0.714,"repost_share":0.071,"time_to_fill_p50_days":51,"computed_at":"2026-10-16T05:45:00Z"}},"role":"Leadership","role_family":"Leadership","seniority":"lead","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["London, United Kingdom","Stockholm, Sweden"],"countries":["GB","SE"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":96000,"max_usd":209000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":59},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Machine Learning","optional":false},{"name":"NLP","optional":false},{"name":"Recommender Systems","optional":false}],"status":"live","first_seen_at":"2026-10-06T14:17:22Z","employer_posted_date":"2026-10-06","last_verified_at":"2026-10-16T21:29:20Z","board_verified":true,"closed_at":null,"days_open":10,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":10},"description":"We design Spotify's consumer experience-end to end, moment to moment, across every screen, platform, and partner integration. Our mission is to make listening feel effortless, personal, and joyful for billions of users around the world. That means turning complexity into clarity across hundreds of touchpoints-from our mobile and desktop apps to the smart speakers, TVs, cars, and integrations where Spotify shows up every day. If it touches a consumer, we shape it. We bring deep insight into human behavior, design, and technology to craft experiences that feel intuitive, expressive, and unmistakably Spotify.\nYou'll lead a senior-heavy group of 10-12 machine learning engineers, including Staff engineers, who team up dynamically to solve high-priority business problems while staying deep in content understanding (audio, video and text). This is a player-coach role with a strong strategic remit: you'll shape where the group goes next, grow our audio understanding expertise over the long term, and help the team scale through thoughtful, practical use of AI in everyday engineering work.\nWhat You'll Do\nLead, coach and grow a group of 10+ senior and Staff machine learning engineers who team up dynamically around business problems while staying deep in their domain.\nSet technical and team strategy for multiple content understanding problems and turn it into clear, achievable plans.\nOwn delivery of high-priority company initiatives, from shaping the problem through to measurable impact for listeners.\nStay close to the technology as a player-coach. Lead technical strategy, reviewing designs, guiding modelling and retrieval choices, and contributing hands-on where it helps the team most.\nDefine and champion a practical point of view on how ML engineers use AI tools in their day-to-day work, and help the team realise real productivity gains.\nPartner with product, design, research and other engineering leaders across Spotify to align priorities and share context.\nWho You Are\nYou have deep machine learning expertise and Staff-level technical judgement, and you're comfortable getting hands-on when it matters.\nYou bring experience across NLP, audio / music content understanding and recommender systems.\nYou have a track record of managing engineering teams while delivering complex, cross-functional initiatives.\nYou enjoy coaching senior and Staff engineers, and you help experienced people grow their impact.\nYou have a clear, informed point of view on using AI to improve how ML engineers work, and you can inspire a team to adopt it.\nYou think strategically, communicate clearly, and can balance long-term bets with near-term delivery.\nWhere You'll Be\nThis role is based in London or Stockholm.\nWe offer the flexibility to work where you work best! 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