{"id":4052625,"url":"https://alion.io/job/hook-music-research-scientist-recommendation-systems","title":"Research Scientist, Recommendation Systems","company":{"id":680023,"name":"Hook Music","domain":"hookmusic.com","url":"https://alion.io/company/hookmusic","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"inferred_company_offices","remote_working_hours":null,"hiring_geo_confidence":"inferred","locations":[],"countries":[],"hiring_countries":["US"],"hiring_countries_total":1,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Recommender Systems","optional":false}],"status":"live","first_seen_at":"2026-11-10T22:02:16Z","employer_posted_date":"2026-11-10","last_verified_at":"2026-11-14T19:15:32Z","board_verified":true,"closed_at":null,"days_open":3,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":3},"description":"About Hook\nHook is a social music platform, backed by top-tier investors, building the next generation of music discovery, fan expression, and creator growth. We turn the songs people love into sounds they can play with, enabling fans and creators to reimagine music through intuitive, remix-friendly experiences with zero learning curve. By partnering directly with artists, labels, and rightsholders, Hook ensures music is discovered, shared, and expressed in ways that respect and reward the people behind it. At Hook, music isn’t just consumed. It’s experienced, expressed, and made personal.\nRole Overview\nWe are looking for a Research Scientist to design, develop, and advance state-of-the-art recommendation systems that power personalized user experiences at scale. In this role, you will conduct applied research, translate theoretical insights into production-ready models, and partner closely with engineering and product to drive measurable impact.\nYou’ll work on problems such as ranking, personalization, user modeling, exploration-exploitation, and representation learning, using real-world data and user-generated content.\nResponsibilities\nDesign, implement, and evaluate machine learning models for recommendation, ranking, and personalization\n\nConduct applied research to improve model quality, robustness, and efficiency\n\nDevelop and execute experimentation strategies using offline evaluation and online testing\n\nWork with complex datasets to understand user behavior and system performance\n\nCollaborate with engineering and product teams to transition research into production systems\n\nShare research results in clear, accessible ways with both technical and non-technical audiences\n\nStay informed about advances in recommendation systems and related ML methodologies\n\nQualifications\nAdvanced degree (PhD or MS) in Computer Science, Machine Learning, Statistics, or a related field, or equivalent experience\n\nExperience developing recommendation, ranking, or personalization models for user-generated content.\n\nStrong foundation in machine learning, statistics, and data analysis\n\nProficiency in Python and modern ML frameworks (e.g., PyTorch)\n\nAbility to conduct independent research and collaborate effectively in team environments\n\nBonus Qualifications\nPrior publications or submissions to RecSys or closely related venues\n\nExperience working with large-scale data and computational systems\n\nExperience with representation learning, sequence modeling, or large-scale optimization\n\nExperience transitioning research prototypes into production systems\n\nWhat We Offer\nOpportunity to shape product direction through data and cutting-edge research\n\nFreedom to shape research direction and problem selection\n\nWork closely with teammates across research, engineering, and product as the organization grows.\n\nSupport for continued learning and professional growth\n\nCompetitive compensation and benefits","description_format":"text","description_chars":2918,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"master","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Music Industry","Blogging & Newsletter Platforms"],"lifecycle":[{"event":"open","at":"2026-11-11T02:39:49Z"}],"visa":[],"liveness":{"score":86,"band":"hot","label":"Hiring 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