Staff MLOps Engineer

NBCUniversal is one of the world's leading media and entertainment companies. We create world-class content, distribute it across film, television, and streaming, and bring it to life through global theme park destinations, consumer products, and experiences. Our brands include NBC, NBC News, NBC Sports, Telemundo, NBC Local Stations, Bravo, and Peacock. We produce premier filmed entertainment through Universal Pictures, DreamWorks Animation, Focus Features, and Universal Studio Group, and operate theme parks worldwide, including Universal Orlando Resort and Universal Studios Hollywood. NBCUniversal is a subsidiary of Comcast Corporation.

About the role

We are seeking a Staff MLOps Engineer with experience building and scaling infrastructure for large 2D and 3D media datasets. You will be responsible for the "backbone" of our machine learning lifecycle, ensuring that our data pipelines are automated, reproducible, and performant at scale.

Responsibilities

• Cross-Functional Coordination: Work with partner ML and Annotation engineers and TPMs to spec out infrastructure and training requirements.
• Pipeline Automation: Design and maintain robust CI/CD and CT (Continuous Training) pipelines for complex multimodal models.
• Data Lifecycle Management: Implement versioning and storage strategies for massive 2D/3D datasets to ensure reproducibility and high-throughput access.
• Monitoring & Observability: 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 applied machine learning.
• Prior experience in industries with complex multi-disciplinary teams such as robotics, smart grids, precision agriculture, game development, or aerospace.

Skills

• Core Tools: Fluency with Python, Git, and the Unix shell.
• Containerization & Orchestration: Deep familiarity with Docker, Kubernetes, and workflow orchestrators (e.g., Airflow, Prefect, or Kubeflow).
• Ecosystem: 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.
• Attributes: High attention to detail regarding system reliability and data security; ability to translate abstract ML requirements into concrete, scalable cloud or on-prem infrastructure.

Benefits

• Medical, dental, and vision insurance.
• 401(k) retirement plan.
• Paid leave.
• Tuition reimbursement.
• A variety of discounts and perks.

Pay

Salary range: $220,000 – $260,000 + 10% bonus eligibility.