Senior Machine Learning Engineer
About Playabl
Playabl is the TikTok for user-generated games — where anyone can play, create, publish, and monetize games. Discovery and personalization are core to how creators find an audience and how players find their next favorite game.
About the Role
We're looking for a Senior Machine Learning Engineer to own search and recommendation systems for Playabl's consumer product. You'll build the models and infrastructure that power what users see in feed, search, discovery, and “continue playing” — especially in a fast-moving UGC catalog. This is a senior IC role for someone who has shipped real ranking, search, or discovery systems in production for consumer apps.
What You Will Own
- Build and improve recommendation and search across feed, discovery, search, and continuation surfaces
- Own retrieval and ranking: candidate generation, embeddings, two-tower models, features, and serving quality
- Design, launch, and analyze experiments; iterate from measurable outcomes
- Improve cold-start quality for new users and new content
- Build user, content, creator, and session representations from behavioral signals
- Partner with product and engineering on metrics, experimentation, and distribution
- Ship practical ML systems with monitoring and clear evaluation
What We Are Looking For
- 5+ years building production ML systems with senior ownership of rec/search/ranking
- Hands-on experience with consumer-facing recommendation or search at scale
- Strong intuition for relevance, retention, engagement, and content distribution
- Solid engineering across modeling, pipelines, backend integration, and online serving
- High ownership and clear communication in ambiguous product environments
Nice to Have
- LLM-powered ranking, semantic search, or multimodal content understanding
- UGC / creator marketplace or rapidly changing catalogs
- Explore/exploit, bandits, or long-term value optimization
- Startup or 0-to-1 ML infrastructure experience
Benefits
- Competitive salary and meaningful equity
- Remote-first team
- Health coverage where applicable