Staff MLOps Engineer
$220,000–$260,000 year
RemoteUnited States
Job Summary
Design and maintain robust CI/CD and CT pipelines for complex multimodal models, ensuring data pipelines are automated, reproducible, and performant at scale. Implement versioning and storage strategies for massive 2D/3D datasets to guarantee high-throughput access, while deploying systems to monitor model performance and data drift in production. Collaborate with ML, annotation engineers, and TPMs to specify infrastructure and training requirements, translating abstract machine learning needs into concrete, scalable cloud or on-prem solutions. This Staff MLOps Engineer role supports NBCUniversal's global content distribution across film, television, and streaming platforms.
Required Qualifications
- 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
- High attention to detail regarding system reliability and data security
- Ability to translate abstract ML requirements into concrete, scalable cloud or on-prem infrastructure
Desired Qualifications
- Strong Mathematical Background: Preferred for understanding the resource demands of 3D data transformations
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