ML Ops / AI Infrastructure Engineer

We're seeking an MLOps Engineer to build our AI infrastructure from the ground up, indexing and retrieving petabytes of multimodal data and enabling our creative AI team to push the boundaries of generative AI in production. This is a foundational role where you'll architect and implement the systems that power generative production, from data management to model deployment and monitoring.

Design and build ML infrastructure to ingest, store, index, and retrieve from petabyte-scale media datasets

Work closely with product and creative AI team to understand backend requirements

Design and deploy model fine-tuning and inference infrastructure

Build monitoring and observability systems for AI workloads

Scale data storage and retrieval capabilities with high availability and efficiency

Build data validation and quality assurance pipelines

Monitor and optimize costs across cloud providers

Develop CI/CD pipelines for our backend services

Proven experience with infrastructure as code (Terraform, CloudFormation, etc.)

Familiarity with ML workflow orchestration tools (Airflow, Kubeflow, MLflow, etc.)

In-depth understanding of distributed computing and storage systems

Experience with monitoring and observability tools

Experience designing and shipping flexible domain models and APIs at scale

A track record of delivering efficiency through automation

Able to set, own, and communicate direction in a dynamic environment

Experience in media & entertainment industry

Knowledge of media file formats and image/video processing pipelines

Familiarity with 3D game engines such as Unreal

Experience with on-premise infrastructure and hybrid cloud

Experience with creating agentic systems