Sekai
Senior Machine Learning Engineer, Recommendation
San Francisco, USA · Senior · Full-time · Posted Oct 20, 2026
- Experience
- 5+ years of industry experience building production ML systems.
About the job
Own and improve production search, recommendation, retrieval, and ranking systems that drive content discovery and distribution in Sekai’s consumer app.
What you'll do
- Build recommendation and search systems across feed, discovery, search, and content continuation surfaces.
- Own retrieval and ranking, launch and analyze experiments, and improve relevance for new users, new content, and changing content pools.
- Partner with product, data, and engineering teams to define metrics and ship monitored, evaluated ML improvements.
What they ask for
- 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, including work on engagement-driven consumer products.
- Practical experience with two-tower models, embedding retrieval, candidate generation, ranking, and online/offline evaluation.
- Strong engineering fundamentals across modeling, data pipelines, backend integration, experimentation, and production ML systems.
Nice to have
- Experience with AI recommendation, LLM-powered ranking, semantic search, personalized generation, or AI-native content understanding.
- Experience with UGC ecosystems, multimodal content understanding, explore/exploit methods, or building 0-to-1 ML systems.
Tools
two-tower models, embedding-based retrieval
AI focus
Build AI-native content discovery, including recommendation and search systems; relevant optional experience includes LLM-powered ranking, personalized generation, and AI-native content understanding.
Model-written summary · the original posting is authoritative