Machine Learning Engineer, Ads Personalization

About the role

We are seeking a Machine Learning Engineer to join the PlutoTV pod. You will focus on Channel, Guide, and Schedule personalization to make the FAST (Free Ad-supported Streaming TV) experience feel as dynamic as a premium on-demand service.

Responsibilities

• Modernizing Linear TV: Transforming the static EPG into a personalized, data-driven discovery engine.
• Optimizing the "Lean-Back": Helping users find something to watch immediately, reducing channel surfing friction.
• Global Scale: Impacting the viewing habits of millions of users worldwide.
• Feature Development: Design and deploy ML components for channel ranking and guide personalization.
• FAST Metadata Integration: Working with linear scheduling data to create features that account for "Current" vs "Next" program relevance.
• Vector-Based Similarity: Using Qdrant to group similar channels and content to improve the "More Like This" experience within the guide.
• Model Refinement: Training and iterating on models using TensorFlow/PyTorch, focusing on session-start and watch-time metrics.
• Independent Execution: Owning the delivery of defined tasks within the PlutoTV roadmap, from data exploration to production deployment.

Requirements

• 3+ years in MLE
• Proficiency in Python/SQL
• Experience with TensorFlow/PyTorch and GCP

Qualifications

• Preferred: Knowledge with FAST or Broadcast TV data structures; experience with Qdrant or similar vector databases.