sekai - Senior Machine Learning Engineer, Recommendation
Requirements
• 5+ years of industry experience building production ML systems, with 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 apps. • Experience working on 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 translate 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. • High ownership, fast execution, and clear communication in ambiguous product environments. • Experience with AI recommendation, LLM-powered ranking, semantic search, personalized generation, or AI-native content understanding. • Experience with UGC content ecosystems, creator marketplaces, or rapidly changing content catalogs. • Experience with multimodal content understanding across text, image, video, interaction traces, or generated content. • Experience with explore/exploit, contextual bandits, reinforcement learning, or long-term value optimization. • Startup experience or experience building 0-to-1 ML systems with limited infrastructure.
Responsibilities
• Build and improve recommendation and search systems across feed, discovery, search, and content continuation surfaces. • Own retrieval and ranking systems, including candidate generation, embedding-based retrieval, two-tower models, ranking features, and online serving quality. • Design, launch, and analyze recommendation/search experiments end-to-end, then use the data to iterate quickly. • Improve recommendation quality for new users, new content, and fast-changing content pools. • Build user, content, creator, and session-level representations from behavioral signals. • Partner with product, data, and engineering teams to define metrics, run experiments, and ship measurable improvements to retention, engagement, and content distribution. • Build practical ML systems that can move from prototype to production quickly, with clear monitoring and evaluation. • Help shape the long-term ML architecture for AI-native content discovery.
Benefits
• Top compensation package, including competitive salary and meaningful equity. • Remote-first team. • Comprehensive health insurance and benefits. • If you are excited about building at the frontier of AI, consumer social, and interactive entertainment, we would love to hear from you. • At Sekai, you will work with an AI-native team, move fast, own meaningful problems, and have the flexibility to explore new ideas from an early stage.
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