AI Content Recommendation Lead

Talmion Data

Hybrid · $130k – $160k / year · Full-time · Posted 5 months ago

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About the role

Content recommendation drives 60% of engagement on our client platforms. When the algorithm works well, users discover content they love. When it doesn't, they see the same popular items everyone else sees and eventually lose interest. The difference between good and great recommendations is the difference between a growing platform and a stagnant one. You'll lead the recommendation systems team: building collaborative filtering models that capture nuanced user preferences, designing exploration strategies that balance user satisfaction against content diversity, and developing the evaluation framework that measures recommendation quality beyond click-through rates — including long-term engagement, content creator fairness, and filter bubble mitigation. Recommendation systems create feedback loops. Popular content gets recommended more, which makes it more popular, which crowds out new creators. You'll design algorithms that explicitly counteract these dynamics, giving emerging content a fair chance while keeping established content performing for the users who want it.

Responsibilities

Lead recommendation systems development across multiple client platforms
Build collaborative filtering models capturing nuanced user preferences
Design exploration strategies balancing satisfaction, diversity, and creator fairness
Develop evaluation frameworks beyond CTR — engagement, diversity, filter bubble metrics
Counteract popularity feedback loops giving emerging content fair exposure

Requirements

5+ years in recommendation systems with team leadership experience
Strong PyTorch and Spark skills for large-scale collaborative filtering
Deep understanding of recommendation evaluation and exploration-exploitation tradeoffs
Experience with fairness and diversity in algorithmic content curation
Track record improving platform engagement through recommendation improvements