About the Role
DAMAC AI is running NVIDIA NCP-compliant GPU infrastructure — B300/GB300 Blackwell clusters. Someone needs to build the platform layer that turns that raw compute into something data scientists and ML engineers can actually use. That’s this role.
You will design and build the orchestration, scheduling, and tooling layer that sits between GPU hardware and AI workloads — Kubernetes-based GPU orchestration, MLOps enablement, platform observability, and developer experience. This is greenfield platform engineering at the hardware-to-workload boundary.
Design AI platform architecture bridging GPU hardware and workload layers
Build Kubernetes-based GPU orchestration — scheduling, resource allocation, multi-tenancy
Key Responsibilities
- Build self-service MLOps tooling for data scientists and ML engineers
- Own platform observability and performance monitoring
- Implement platform security and compliance for multi-tenant environments
- Drive automation and developer experience improvements
How to Apply
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