Senior Machine Learning Engineer, Recommendation

You'll own search and recommendation systems that decide what users see, search for, continue playing, and how quality content reaches the right audience.

• Build and improve recommendation and search systems across feed, discovery, search, and content-continuation surfaces
• Own retrieval and ranking, 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 iterate quickly on the results
• 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 and ship measurable improvements to retention and engagement

• 5+ years of experience building production recommendation, search, or ranking systems for consumer apps
• Hands-on experience with embedding-based retrieval and ranking architectures (e.g. two-tower models)
• Comfortable moving from prototype to production quickly, with clear monitoring and evaluation

Tech stack: Python, ranking and recommendation systems, two-tower models, embedding retrieval, LLMs, TensorFlow/PyTorch, ML pipelines, A/B testing

Compensation: $160K–$250K plus highly competitive equity. Visa sponsorship available (TN, H-1B transfers, and new H-1Bs considered case-by-case).

Work policy: remote-first, working Pacific time hours.

Interview process: initial screen, two technical rounds, final round.