Staff MLOps Engineer – Ingénieur(e) MLOps expert(e)

🔥 18 hours ago

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NBCUniversal

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 2004

📱 Media

Media • Entertainment

NBCUniversal is a leading global media and entertainment company known for creating and distributing content across a variety of platforms. With over 100 years of experience, it is a part of Comcast and encompasses brands like Peacock, NBC Sports, and many others to educate, entertain, and empower audiences around the world. The company is involved in television broadcasting, film production, and theme parks, and is also recognized for its initiatives in technology and corporate social responsibility. NBCUniversal is committed to innovation and social impact, making it a vibrant workplace for media and tech professionals.

📋 Description

• 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

🏖️ Benefits

• Health insurance • Equal employment opportunities • Professional development