Principal Machine Learning Engineer

ParamountNew York, NY

About The Position

Paramount Streaming is building the next generation of personalization and discovery across global platforms. This role leads high-impact machine learning initiatives focused on optimizing the Paramount+ sign-up and Pluto TV registration flow. This position shapes how millions of viewers discover films, series, live sports, and news on Paramount+, Pluto TV, and our future streaming products.This is a highly visible technical leadership role facilitating innovation at the intersection of ML modeling, retrieval and ranking systems, multi-modal embeddings, multi-armed bandits, experimentation, and real-time user comprehension.

Requirements

  • 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.

Responsibilities

  • 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.

Benefits

  • medical
  • dental
  • vision
  • 401(k) plan
  • life insurance coverage
  • disability benefits
  • tuition assistance program
  • PTO

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What This Job Offers

Job Type

Full-time

Career Level

Mid Level

Education Level

No Education Listed

Number of Employees

5,001-10,000 employees

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