Director Of Product, Algorithms & Personalization Full Time

Job Overview

Every day, millions of people meet, form bonds, and build communities in VRChat. Our job is to help users connect with people and experiences they’ll love, faster and more reliably, through world-class algorithms.

The Director of Product, Algorithms & Personalization is an individual contributor role on VRChat’s product team. This role will lead VRChat’s end-to-end algorithm and personalization strategy across:

Matchmaking: helping users find people they’re likely to become friends with
Discovery: ranking and recommending worlds, groups, and events to drive meaningful engagement and belonging
Trust & Safety: models that detect predatory and toxic behavior, ensuring our users can have high quality interactions and safe experiences.

You will partner closely with ML/Engineering, Data Science, Design, Community, Trust & Safety, Policy, Legal, and Operations to design and ship algorithmic systems that improve user experience while managing platform integrity, safety, and privacy tradeoffs.

This role has significant executive visibility, with regular updates to senior leadership and, when needed, the board.

What Algorithms & Personalization includes at VRChat
Building and evolving recommender systems (retrieval, ranking, and re-ranking) for worlds, groups, and events
Designing social matchmaking experiences and models
Developing user and content understanding: embeddings, taxonomies, intent signals, quality signals, and cold-start strategies
Shipping real-time and session-aware personalization
Establishing measurement and experimentation: offline metrics, online A/B testing, guardrails, long-term impact
Building the product and platform foundations: logging, feature stores, model iteration loops, and ops tooling for diagnostics

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.

Experience, Skills & Qualifications
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.