6 hours ago
Responsibilities
- Build and improve recommendation and search systems for feed, discovery, search, and content-continuation surfaces.
- Own candidate generation, embedding-based retrieval, two-tower models, ranking features, and online serving quality.
- Design, launch, and analyze recommendation and search experiments end to end.
- Build user, content, creator, and session-level representations from behavioral signals.
- Partner with product, data, and engineering teams to define metrics and ship improvements to retention, engagement, and content distribution.
- Develop practical ML systems that move from prototype to production with monitoring and evaluation.
- Help shape the long-term ML architecture for AI-native content discovery.
Requirements
- At least 5 years of industry experience building production ML systems, including senior-level ownership of recommendation, search, ranking, ads ranking, feed ranking, or content discovery systems.
- Hands-on experience building recommendation or search systems for consumer applications.
- Experience with entertainment, social, gaming, short-form content, creator, or other engagement-driven consumer products.
- Strong practical experience with two-tower models, embedding retrieval, candidate generation, ranking, and online/offline evaluation.
- Strong product intuition around relevance, retention, engagement, satisfaction, cold start, and content distribution.
- Ability to turn messy user behavior into useful modeling signals and practical product improvements.
- Strong engineering fundamentals across modeling, data pipelines, backend integration, experimentation, and production ML systems.
- Experience with AI recommendation, LLM-powered ranking, semantic search, personalized generation, UGC ecosystems, multimodal content understanding, explore/exploit, contextual bandits, reinforcement learning, or long-term value optimization is a plus.
- Startup experience or experience building zero-to-one ML systems with limited infrastructure is a plus.
Benefits
- Remote-first work across all positions.
- Competitive salary and meaningful equity.
- Comprehensive health insurance and benefits.
- Opportunity to work with an AI-native team on early-stage consumer social and interactive entertainment products.
Tech Stack
iOS
Categories
