Lead the design and development of personalization in the P+ sign-up flow and Pluto TV registration flows.
Own end-to-end machine learning pipelines—from data and feature engineering to training, deployment, serving, and monitoring.
Partner closely with product, design, content, platform engineering, and data science to define roadmaps and deliver measurable user outcomes.
Advance our semantic search and browse experience through state-of-the-art embeddings, query understanding, and domain-specific model architectures.
Establish high-integrity experimentation practices, improve offline→online correlation, and guide feature rollouts with strong scientific rigor.
Mentor engineers and scientists, develop technical talent, and help shape the culture of our growing Applied ML organization.

7–10+ years of experience in machine learning engineering, applied science, recommender systems, multi-armed bandits, or large-scale search/ranking systems.
Demonstrated expertise deploying ML systems in high-traffic, real-time production environments.
Deep knowledge of modeling techniques such as representation learning, multi-task learning, multi-modal embeddings, contextual bandits, and session modeling.
Strong fluency in experimentation methodology, A/B testing, causal reasoning, and metric design.
Experience leading and mentoring technical teams; ability to drive strategy while remaining hands-on.
Proficiency with modern ML tooling (PyTorch, TensorFlow), big-data environments (Spark, Beam, BigQuery), and production MLOps workflows.

Principal Machine Learning Engineer

Key skills