Research Scientist, Recommendation Systems

Job Description:

• Design, implement, and evaluate machine learning models for recommendation, ranking, and personalization
• Conduct applied research to improve model quality, robustness, and efficiency
• Develop and execute 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 systems
• Share research results in clear, accessible ways with both technical and non-technical audiences
• Stay informed about advances in recommendation systems and related ML methodologies.

Requirements:

• Advanced degree (PhD or MS) in Computer Science, Machine Learning, Statistics, or a 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 (e.g., PyTorch)
• Ability to conduct independent research and collaborate effectively in team environments
• Prior publications or submissions to RecSys or closely related venues (preferred)
• Experience working with large-scale data and computational systems (preferred)
• Experience with representation learning, sequence modeling, or large-scale optimization (preferred)
• Experience transitioning research prototypes into production systems (preferred).

Benefits:

• Competitive base salary
• Meaningful equity ownership
• Opportunity to build and lead growth at a fast-growing consumer company.

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