Software Engineer

Requirements:

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• 5+ years of experience building distributed systems or infrastructure platforms with deep Kubernetes expertise.
• Strong programming skills in Go and/or Python.
• Familiarity with Kubernetes controller development frameworks such as Kubebuilder, Operator SDK, or controller-runtime.
• Deep understanding of Kubernetes internals, including the API server, etcd, scheduler, controller manager, and kubelet.
• Hands-on experience designing Kubernetes networking, including Gateway API, CNI plugins, service load balancing, and hybrid cloud architectures.
• Experience designing and operating multi-NIC Kubernetes clusters using NVIDIA Network Operator, SR-IOV device plugins, or equivalent tooling.
• Strong understanding of RDMA networking protocols and NCCL configuration for distributed GPU workloads.
• Experience with Kubernetes GPU scheduler frameworks and GPU pool management, including MIG partitioning and preemption policies.
• Hands-on experience deploying and operating KubeRay for distributed Ray workloads.
• Experience with GPU asset lifecycle management, bare-metal provisioning automation, and GitOps-based CD tooling such as Argo CD.
• Familiarity with GPU technologies, including NVIDIA CUDA, NVLink, NVSwitch, device plugins, and the GPU Operator ecosystem.
• Experience with observability tooling such as Prometheus, Grafana, and OpenTelemetry.
• Strong debugging and performance optimisation skills across GPU driver stacks, RDMA networking, and distributed Kubernetes infrastructure.

Skills

CUDA, GPU, Go, Golang, K8s, Kubernetes, NVIDIA, Python