ML Ops / AI Infrastructure Engineer
Core
Architect and implement AI infrastructure for indexing, retrieving, and managing petabyte-scale multimodal media datasets to power generative AI in production.
Role type
MLOps / AI Infrastructure Engineer
Builds
Data ingestion, storage, indexing, retrieval systems; model fine-tuning and inference infrastructure; CI/CD pipelines; monitoring and observability systems.
Domain
Media & Entertainment / Generative AI / Cloud Infrastructure
Deliverable
production ML models | infrastructure
Required skills
Infrastructure as Code (Terraform, CloudFormation), ML workflow orchestration (Airflow, Kubeflow, MLflow), distributed computing and storage systems, monitoring and observability tools, scalable API design, automation
Preferred skills
Media & entertainment industry experience, media file formats and image/video processing pipelines, 3D game engines (Unreal), on-premise and hybrid cloud infrastructure, agentic systems
Technologies
Terraform, CloudFormation, Airflow, Kubeflow, MLflow, Unreal
Responsibilities
Design and build ML infrastructure for petabyte-scale media datasets; Design and deploy model fine-tuning and inference infrastructure; Build monitoring and observability systems for AI workloads; Scale data storage and retrieval capabilities; Build data validation and quality assurance pipelines; Monitor and optimize costs across cloud providers; Develop CI/CD pipelines for backend services