Staff MLOps Engineer

NBCUniversal is one of the world's leading media and entertainment companies. We create world-class content, which we distribute across our portfolio of film, television, and streaming, and bring to life through our global theme park destinations, consumer products, and experiences. We own and operate leading entertainment and news brands, including NBC, NBC News, NBC Sports, Telemundo, NBC Local Stations, Bravo, and Peacock, our premium ad-supported streaming service. We produce and distribute premier filmed entertainment and programming through our powerhouse film and television studios, including Universal Pictures, DreamWorks Animation, and Focus Features, and the four global television studios under the Universal Studio Group banner, and operate industry-leading theme parks and experiences around the world through Universal Destinations & Experiences, including Universal Orlando Resort, home to Universal Epic Universe, and Universal Studios Hollywood. NBCUniversal is a subsidiary of Comcast Corporation. Visit www.nbcuniversal.com for more information.

Our impact is rooted in improving the communities where our employees, customers, and audiences live and work. We have a rich tradition of giving back and ensuring our employees have the opportunity to serve their communities. We champion an inclusive culture and strive to attract and develop a talented workforce to create and deliver a wide range of content reflecting our world.

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.

Key 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.

• 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.
• Professional Experience: Proven experience as an MLOps Engineer in a fast-paced environment in applied machine learning.
• Industry Context: Prior experience in industries with complex multi-disciplinary teams such as robotics, smart grids, precision agriculture, game development, or aerospace.
• Technical Proficiency:
  • 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:
  • Conscientiousness: High attention to detail regarding system reliability and data security.
  • Systems Thinking: Ability to translate abstract ML requirements into concrete, scalable cloud or on-prem infrastructure

This position is eligible for company sponsored benefits, including medical, dental and vision insurance, 401(k), paid leave, tuition reimbursement, and a variety of other discounts and perks. Learn more about the benefits offered by NBCUniversal by visiting the Benefits page of the Careers website. Salary range: $220,000k - 260,000 + 10% (bonus eligibility).

As part of our selection process, external candidates may be required to attend an in-person interview with an NBCUniversal employee at one of our locations prior to a hiring decision. NBCUniversal's policy is to provide equal employment opportunities to all applicants and employees without regard to race, color, religion, creed, gender, gender identity or expression, age, national origin or ancestry, citizenship, disability, sexual orientation, marital status, pregnancy, veteran status, membership in the uniformed services, genetic information, or any other basis protected by applicable law.

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