# Senior Machine Learning Engineer, Recommendation

**Company:** [Sekai](https://hotfix.jobs/companies/sekai)
**Location:** Remote
**Role:** ML Engineering
**Experience:** 5+ years
**Skills:** Machine Learning, Recommendation Systems, Search Systems, Two-Tower Models, Embedding Retrieval, Candidate Generation, Ranking Models, Experimentation, Data Pipelines, Production Ml Systems
**Posted:** 2026-06-08

> Senior IC role owning search and recommendation systems for a consumer social platform. Build retrieval, ranking, and discovery models that drive user engagement and content distribution.

## Job Description

## What You Will Own
- 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.

## What We Are Looking 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.
- 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.

## Nice to Have
- 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.

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**Apply:** https://hotfix.jobs/jobs/bc8a81b3-f3da-4e09-9696-9b39cc056f0a
**Canonical:** https://hotfix.jobs/jobs/bc8a81b3-f3da-4e09-9696-9b39cc056f0a