Senior Recommendation Engineer

What you'll do

• Own feed recommendation systems from candidate generation through experimentation and monitoring.
• Design event-triggered engagement and customer-to-professional matching systems, including fairness constraints.
• Define evaluation frameworks that account for downstream outcomes and negative signals; contribute learnings to pricing and intent models.

What they ask for

• 5+ years of machine-learning or software engineering, including 3+ years shipping production recommendation or ranking systems.
• Built and operated a consumer-scale ranking system for millions of users, including candidate generation, ranking, and monitoring.
• Substantial online experimentation experience; production deployment of an uplift, causal, or counterfactual model, or a rigorous account of why click-based objectives are unsuitable for rare, high-cost decisions.
• Strong Python and at least one of Java, Scala, or Go; production experience with feature stores and streaming pipelines.

Nice to have

• Feed or notification ranking at a content or media company; two-sided marketplace matching with fairness or exposure constraints in production.
• Experience in low-frequency, high-consequence domains, or publications/open-source contributions in recommendation, causal inference, or marketplace design.

Pay

$150,000 — $300,000 USD annual base salary

Tools

Python, Java, Scala, Go

AI focus

Builds recommendation and ranking systems, event-triggered engagement with propensity and uplift modeling, and customer-provider matching; contributes learnings to pricing and intent models.