{"id":1538902,"url":"https://alion.io/job/spotify-machine-learning-engineering-manager-music","title":"Machine Learning Engineering Manager - Music","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":79,"open_postings":7,"ghost_share":0,"stale_share":0.857,"repost_share":0,"time_to_fill_p50_days":55,"computed_at":"2026-10-01T05:45:00Z"}},"role":"Leadership","role_family":"Leadership","seniority":"lead","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":{"label":"ET","utc_offset_min":-5,"utc_offset_max":-5},"hiring_geo_confidence":"structured","locations":["New York, United States"],"countries":["US"],"hiring_countries":["US"],"hiring_countries_total":1,"salary":null,"salary_estimate":{"min_usd":178000,"max_usd":302000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":153},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Machine Learning","optional":false}],"status":"live","first_seen_at":"2026-09-29T17:35:39Z","employer_posted_date":"2026-09-29","last_verified_at":"2026-10-01T18:00:09Z","board_verified":true,"closed_at":null,"days_open":2,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":2},"description":"As the Engineering Manager of the Oasis Squad, you’ll lead a multidisciplinary team of machine learning, data, and backend engineers building ML systems at the heart of how Spotify shapes and delivers music experiences.\nOasis needs a people leader with significant technical machine learning depth who can help the team navigate complex technical strategy, shifting business needs, and high-impact cross-functional decisions. A great manager for this team will give experienced engineers meaningful autonomy while staying deeply engaged in their technical work. You’ll have the ML expertise to assess technical tradeoffs, steer the team toward decisions, and represent its technical direction with senior partners across Personalization, Product, and the music business. This is a role for someone who enjoys being close to both the people and the work: coaching engineers, creating clarity amidst constant change, and enabling a high-performing team to move quickly without adding unnecessary process.\nIf this role excites you but you don't meet every requirement, we'd still love to hear from you. We welcome candidates from all backgrounds.\nWhat You'll Do\nLead, coach, and develop a multidisciplinary team of ML, data, and backend engineers, giving experienced ICs meaningful autonomy while providing active mentorship and coaching where needed.\n\nProvide technical leadership on complex ML systems, engaging deeply enough with modeling strategy and implementation to challenge assumptions, assess tradeoffs, identify risks, and help the team make decisions.\n\nRepresent and advocate for the team with cross-functional stakeholders across business, product, insights, and the personalization mission, balancing technical concerns with business needs.\n\nEmpower engineers to own technical decisions, but recognize when the team needs you to provide direction, resolve a tradeoff, or make the decision yourself.\n\nBe the point of contact for requests from cross-functional partners, filtering the important updates to the team and preserving their heads down time.\n\nOwn healthy delivery, including prioritization, capacity management, operational health, and reliable execution, while favoring lightweight processes that help the team move quickly and learn.\n\nStay close to the engineering craft and act as a player-coach when useful, including contributing hands-on to technical problem solving and engineering work.\n\nHelp the team use AI effectively in engineering workflows and identify opportunities for AI to improve both how we build and the ML systems we create.\n\nHire and onboard engineers as the team evolves, building the capabilities and knowledge distribution needed for the team to remain resilient over time.\n\nWho You Are\nExperience managing engineers and a demonstrated track record of developing and managing technical ICs.\n\nYou have a solid background in machine learning and can engage credibly in modeling strategy, ML system design, and technical discussions with experienced ML practitioners.\n\nYou can independently assess ML strategies and technical tradeoffs, challenge assumptions, and clearly represent a technical direction with both technical and non-technical stakeholders.\n\nYou are comfortable operating in an environment where technical strategy must account for evolving product and business needs, and can create clarity for your team through sudden shifts in direction.\n\nYou build trust with experienced engineers by giving them autonomy and avoiding unnecessary oversight, while remaining close enough to their work to coach effectively, understand risks, and step in when needed.\n\nYou view yourself as your team’s advocate.\n\nYou are a thoughtful leader who knows when to facilitate a decision, when to let the team decide, and when to make the decision yourself.\n\nYou favor lightweight, purposeful processes over process for its own sake. You can maintain a strong understanding of work, risks, and delivery without creating unnecessary overhead for the team.\n\nYou are comfortable making calculated tradeoffs, learning through iteration, and helping teams move quickly while maintaining appropriate technical and operational standards.\n\nYou can manage substantial technical, product, and business dependencies with partner teams and build credibility with senior cross-functional stakeholders.\n\nYou are comfortable using AI tools and have a point of view on how AI can improve engineering effectiveness and evolve ML-powered products.\n\nYou value healthy disagreement, clear ownership, accountability, and an inclusive environment where people can do their best work.\n\nExperience with data engineering and backend is a plus.\n\nWhere You'll Be\nWe offer you the flexibility to work where you work best! For this role, it can be within the North America region in which we have a work location.\n\nThis team collaborates across the Eastern time zone","description_format":"text","description_chars":4874,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Media & Entertainment","Advertising","Audio Production","Podcasting"],"lifecycle":[{"event":"open","at":"2026-09-30T20:08:15Z"}],"liveness":{"score":90,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.903,"p_room":1,"age_days":1,"expected_fill_days":55,"reasons":["conf:9","velocity","win:early"],"computed_at":"2026-10-01T05:45:00Z"},"pay":null,"html_url":"https://alion.io/job/spotify-machine-learning-engineering-manager-music","json_url":"https://alion.io/job/spotify-machine-learning-engineering-manager-music.json","meta":{"generated_at":"2026-10-01T21:15:23Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":3876,"day_limit":5000,"remaining_today":1124,"minute_limit":60,"resets_at":"2026-10-02T00:00:00Z"}}}