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DirectorFull-timeRustRailsData ScienceML
Salary Range
$102,000 - $138,000 /year
This salary is estimated based on similar roles. The actual salary may vary.
About the Role
We are looking for a Director of Product, Algorithms & Personalization to join VRChat’s product team. This role will lead VRChat’s end-to-end algorithm and personalization strategy across matchmaking, discovery, and trust & safety.
Key Responsibilities
- →Own the product strategy for personalization, matchmaking, and discovery across VRChat, including worlds, groups, events, and social connections.
- →Lead the roadmap for algorithmic systems spanning candidate generation, ranking, diversity and novelty controls, exploration vs. exploitation, and session- and context-aware recommendations.
- →Partner closely with ML/Engineering and Data Science to deliver production-grade models and pipelines, covering data instrumentation, feature development, evaluation, and iteration.
- →Design user-facing experiences that translate algorithmic capabilities into clear, differentiated user value.
- →Define and operationalize success metrics across relevance, retention, social outcomes (e.g., friendship formation), and ecosystem health (e.g., creator success), with strong guardrails.
- →Own experimentation end-to-end, from hypothesis generation and test design to analysis, rollout, and ongoing tuning.
- →Ensure system quality and integrity by addressing spam, manipulation, low-quality content, feedback loops, and unintended consequences, in partnership with Trust & Safety and Policy.
- →Communicate progress, tradeoffs, and outcomes clearly to executives and cross-functional partners, driving alignment on goals and execution.
Requirements
- ✓7+ years of product management experience on large-scale consumer platforms.
- ✓Deep experience building algorithm-driven products: personalization, ranking, recommender systems, feeds, search/discovery, or matchmaking.
- ✓Strong fluency in experimentation and measurement: A/B testing, counterfactual thinking, metrics design, and causal reasoning basics.
- ✓Ability to work effectively with technical teams on ML systems: model lifecycle, data pipelines, evaluation, deployment/monitoring, and iteration.
- ✓Strong product judgment around tradeoffs: relevance vs. diversity, short-term engagement vs. long-term satisfaction, growth vs. ecosystem health.
- ✓Excellent communication skills. You can translate complex technical concepts into crisp decisions and narratives.
