Senior GPU Cloud K8s Architect

Bitdeer Technologies Group; San Jose (CA); On-site; USD 180,000 - 300,000; Full time

Job summary

Bitdeer is building an AI-operated GPU cloud. You will design, deploy, and operate the Kubernetes-based control plane that enables topology-aware scheduling, self-healing, and automated remediation for GPU workloads.

In year one you will optimize multi-tenant clusters, implement BMaaS provisioning, and integrate Prometheus/Grafana monitoring. You will work with Go/Python to develop operators and CRDs that drive autonomous workflows.

Qualifications

• 5+ years in Kubernetes operations with hands-on GPU workload management
• Deep expertise with Nvidia GPU operator, device plugin, and GPU scheduling in K8S
• Experience with topology-aware scheduling and GPU resource management
• Hands-on experience building multi-tenant K8S platforms with strong isolation
• Experience with bare-metal provisioning and lifecycle automation
• Proficiency in Terraform, Helm, and GitOps workflows (ArgoCD/Flux)
• Strong SRE background: SLI/SLO, incident management, capacity planning
• Experience with Prometheus, Grafana, and alerting at scale
• Programming skills in Go or Python for operator/CRD development
• AIOps mindset: automate remediation as part of the control plane
• Runbook-as-code mindset for executable playbooks

Responsibilities

• Production Kubernetes clusters optimized for GPU workloads (100-10,000 GPUs)
• Nvidia GPU operator, device plugin, MIG configuration, and GPU time-slicing policies
• Topology-aware scheduling: GPU locality, NVLink awareness, network affinity
• CRDs for GPU workload lifecycle management
• AI framework integrations: Slurm on K8S, Ray on K8S, Kubeflow
• Multi-tenant isolation: namespaces, network policies, resource quotas, RBAC, pod security
• BMaaS provisioning: automated onboarding, lifecycle, reclamation
• Terraform providers and modules for infrastructure-as-code across GPU clusters
• SLIs/SLOs for cluster availability and provisioning latency
• Incident management: runbook automation, escalation, post-incident reviews
• Monitoring: Prometheus, Grafana, Alertmanager
• GPU node failure handling: automated drain/cordon/taint and reschedule

Skills

Kubernetes operations

GPU workloads on K8S

Topology-aware scheduling

Multi-tenant platforms

Go or Python

Tools

Terraform

Helm

GitOps

Prometheus

Grafana

Job description

Bitdeer is building an AI-operated GPU cloud. You will design, deploy, and operate the Kubernetes-based control plane that enables topology-aware scheduling, self-healing, and automated remediation for GPU workloads.

In year one you will optimize multi-tenant clusters, implement BMaaS provisioning, and integrate Prometheus/Grafana monitoring. You will work with Go/Python to develop operators and CRDs that drive autonomous workflows.