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About the role

  • MLOps Engineer managing infrastructure for large 2D and 3D media datasets at NBCUniversal. Responsible for automation, reproducibility, and performance of machine learning lifecycles.

Responsibilities

  • Collaborate with partner ML and annotation engineers and TPMs to specify 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 large-scale 2D/3D datasets to ensure reproducibility and high-throughput access.
  • Deploy and operate systems for monitoring model performance and detecting data drift in production environments.

Requirements

  • Graduate degree (Master's or PhD) in Computer Science, Software Engineering, or a related field.
  • 5+ years of experience as an MLOps Engineer in fast-paced applied machine learning environments.
  • Proficient in Python, Git, and the Unix shell.
  • Deep familiarity with Docker, Kubernetes, and workflow orchestrators (e.g., Airflow, Prefect, or Kubeflow).
  • Experience 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.
  • High attention to detail with respect to system reliability and data security.
  • Ability to translate abstract ML requirements into concrete, scalable cloud or on-premises infrastructure.
  • Prior experience working with complex multidisciplinary teams (e.g., robotics, smart grids, precision agriculture, game development, or aerospace).
  • Must be legally authorized to work in Canada.

Benefits

  • Health insurance
  • Retirement plans
  • Paid time off
  • Flexible work arrangements
  • Professional development

Job type

Full Time

Experience level

Lead

Salary

Not specified

Degree requirement

Postgraduate Degree

Tech skills

AirflowCloudDockerKubernetesPythonUnix

Location requirements

RemoteCanada

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