About this role
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 modernize the FAST (Free Ad-supported Streaming TV) experience and make it as dynamic as a premium on-demand service. You will help build the models that select which channels appear in the guide and how content is scheduled to maximize viewer session length.
This role requires deep knowledge of FAST systems and the unique constraints of linear programming. You will implement features within our GCP stack, leveraging Qdrant for content similarity and Post-training RL to optimize the Lean-back viewing experience.
What You'll Do
- Focus on Channel, Guide, and Schedule personalization to maximize viewer session length.
- Help build models that select which channels appear in the guide and how content is scheduled to maximize engagement.
- Implement features within the GCP stack, leveraging Qdrant for content similarity and Post-training RL to optimize the Lean-back viewing experience.
- Transform the static EPG into a personalized, data-driven discovery engine and contribute to PlutoTV's global scalability.
What We're Looking For
- Deep knowledge of FAST systems and the unique constraints of linear programming.
- Experience implementing features within a GCP stack and leveraging Qdrant for content similarity and Post-training RL to optimize the Lean-back viewing experience.
- Ability to contribute to a FAST-led, global-scale product used by millions of users.