Research Scientist, Recommendation Systems

This is a fully remote position, open to applicants in United States.

📋 Description

• Design, develop, and assess machine learning models aimed at recommendation, ranking, and personalization.

• Perform applied research to enhance model quality, robustness, and efficiency.

• Create and implement experimentation strategies utilizing offline evaluation and online testing.

• Analyze complex datasets to gain insights into user behavior and system performance.

• Collaborate with engineering and product teams to integrate research into production systems.

• Present research findings in a clear and accessible manner to both technical and non-technical audiences.

• Keep up-to-date with advancements in recommendation systems and related machine learning methodologies.

⛳️ Requirements

• Advanced degree (PhD or MS) in Computer Science, Machine Learning, Statistics, or a related discipline, or equivalent experience.

• Proven experience in developing recommendation, ranking, or personalization models for user-generated content.

• Strong background in machine learning, statistics, and data analysis.

• Proficient in Python and contemporary ML frameworks (e.g., PyTorch).

• Capability to conduct independent research while collaborating effectively in team settings.

• Prior publications or submissions to RecSys or related forums.

• Experience managing large-scale data and computational systems.

• Familiarity with representation learning, sequence modeling, or large-scale optimization.

• Experience in transitioning research prototypes into production environments.

🏝️ Benefits

• Opportunity to influence product direction through data and innovative research.

• Autonomy to determine research focus and problem selection.

• Collaborate closely with colleagues across research, engineering, and product teams as the organization expands.

• Support for ongoing learning and professional development.

• Competitive salary and benefits package.