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).
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