Research Scientist, Recommendation Systems

Responsibilities

• Design, implement, and evaluate ML models for recommendation, ranking, and personalization
• Conduct applied research to improve model quality, robustness, and efficiency
• Develop experimentation strategies using offline evaluation and online testing
• Work with complex datasets to understand user behavior and system performance
• Collaborate with engineering and product teams to transition research into production
• Share research results with technical and non-technical audiences

Requirements

• PhD or MS in Computer Science, Machine Learning, Statistics, or related field, or equivalent experience
• Experience developing recommendation, ranking, or personalization models for user-generated content
• Strong foundation in machine learning, statistics, and data analysis
• Proficiency in Python and modern ML frameworks such as PyTorch
• Ability to conduct independent research and collaborate in teams

Preferred Qualifications

• Publications or submissions to RecSys or related venues
• Experience with large-scale data and computational systems
• Experience with representation learning, sequence modeling, or large-scale optimization
• Experience transitioning research prototypes into production systems

Benefits

• Opportunity to shape product direction through data and research
• Freedom to shape research direction and problem selection
• Support for continued learning and professional growth
• Competitive compensation and benefits

About the Company

• Hook is a social music platform building next-generation music discovery, fan expression, and creator growth, backed by top-tier investors.