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