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NBCUniversal

Staff MLOps Engineer – Ingénieur(e) MLOps expert(e)

NBCUniversal

Staff MLOps Engineer responsible for building infrastructure for AI/ML at NBCUniversal. Managing large media datasets, deploying models, and automating data pipelines.

Posted 6/30/2026full-timeRemote • 🇨🇦 CanadaLeadWebsite

Tech Stack

Tools & technologies
AirflowDockerKubernetesPythonUnix

About the role

Key responsibilities & impact
  • Develop and own the backbone of our machine learning lifecycle, ensuring that data pipelines are automated, reproducible, and highly performant at scale
  • Work on enabling seamless model training, deployment, and monitoring across complex, multimodal systems, supporting the evolution of cutting-edge AI/ML applications
  • Collaborate with partner ML and Annotation engineers and TPMs to spec out infrastructure and training requirements
  • Design and maintain robust CI/CD and CT (Continuous Training) pipelines for complex multimodal models
  • Implement versioning and storage strategies for massive 2D/3D datasets to ensure reproducibility and high-throughput access
  • Deploy and manage systems for monitoring model performance and data drift in production environments

Requirements

What you’ll need
  • Master's degree in Computer Science, Engineering, Mathematics, or a related field
  • Minimum of 5+ years of relevant industry experience, ideally within a fast-paced, high-growth tech environment
  • Proven experience as an MLOps Engineer in a fast-paced environment in applied machine learning
  • Prior experience in industries with complex multi-disciplinary teams such as robotics, smart grids, precision agriculture, game development, or aerospace
  • Fluency with Python, Git, and the Unix shell
  • Deep familiarity with Docker, Kubernetes, and workflow orchestrators (e.g., Airflow, Prefect, or Kubeflow)
  • Familiarity with collaborative tools such as Jira/Confluence, Slack and a Git server
  • Strong Mathematical Background: Preferred for understanding the resource demands of 3D data transformations

Benefits

Comp & perks
  • Health insurance
  • Equal employment opportunities
  • Professional development

ATS Keywords

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Hard Skills & Tools
Machine Learning LifecycleData Pipeline AutomationModel DeploymentVersioning StrategiesMathematical Analysis
Certifications
Master's Degree in Computer ScienceMaster's Degree in EngineeringMaster's Degree in Mathematics