What are the responsibilities and job description for the ML Ops / AI Infrastructure Engineer position at ZeroSpace?
ZeroSpace is a digital agency and production studio specializing in emerging technologies and real-time 3D for virtual production, CG animation, and immersive experiences. Our unique facility houses the largest fixed-install LED volume on the East Coast, industry-standard Vicon motion capture systems, and a state-of-the-art volumetric capture studio. We're an interdisciplinary team of technologists and artists where technical innovation meets creative vision. Our clients include major film studios, Oscar-winning directors, and the biggest brands in the world.
The Role
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.
In This Role, You Will
The Role
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.
In This Role, You Will
- 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
