About this role
About the Role We are seeking a Senior Machine Learning Engineer to lead the development of our multimodal embedding and retrieval systems that power content discovery across Paramount's video library. In this role, you will own the full lifecycle of multi-modal embedding systems, optimized for text and video understanding, from generation, ingestion and indexing, to retrieval — directly impacting how millions of users discover and engage with short-form clips. You will partner with product leadership, Content and Personalization engineering teams, mentor engineers and serve as a senior technical voice shaping how the platform "sees" and retrieves video clip content at scale. What You'll Do
- Lead development of multimodal embedding and retrieval systems for content discovery across Paramount's video library.
- Own end-to-end lifecycle: generation, ingestion, indexing, and retrieval of high-dimensional vector embeddings.
- Design and implement hybrid retrieval systems combining vector similarity, lexical search, and reranking.
- Collaborate with product, Content and Personalization teams; mentor engineers; influence platform architecture.
- Optimize for latency, throughput, and scalability to serve millions of users. What We're Looking For
- Hands-on systems builder with ownership of pipelines storing, indexing, and querying high-dimensional embeddings.
- Experience designing hybrid retrieval systems (vector similarity, lexical search, reranking).
- Strong background in multimodal video understanding and content representations.
- Ability to translate embedding system tradeoffs into practical system design (latency, accuracy, scalability).
- Experience mentoring engineers and collaborating with cross-functional teams.