Note: The job is a remote job and is open to candidates in USA. Sekai is building an AI-driven consumer platform for interactive content. The Senior Machine Learning Engineer will own and improve search and recommendation systems that power content discovery, user engagement, and distribution.
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
Skills
- 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
Benefits
- Meaningful equity
- Comprehensive health insurance
- Remote-first across all positions
Company Overview
Company H1B Sponsorship