Senior Platform Software Engineer – AI/ML & GPU Infrastructure
Core
Architect and operate the control-plane and scheduling systems for Cisco's AI Compute Platform, managing GPU capacity allocation, multi-cluster orchestration, and workload scheduling for training and inference.
Role type
Senior Platform Software Engineer (Kubernetes/GPU Infrastructure)
Builds
Unified control plane, Kubernetes platform, and GPU scheduling/orchestration tools for AI/ML workloads
Domain
Cloud infrastructure, GPU acceleration, Kubernetes, Distributed Systems
Deliverable
production ML models | infrastructure
Required skills
Kubernetes (control plane, Operators, CRDs), Go, Python, GPU scheduling, Distributed systems architecture, Infrastructure as Code (Terraform), GitOps, CI/CD, Observability (Prometheus, Grafana)
Preferred skills
Multi-cluster federation, NVIDIA/AMD GPU architectures, Topology-aware placement, NCCL, Linux kernel tuning, eBPF, MLOps platforms
Technologies
Kubernetes, OpenShift, Go, Python, Terraform, Splunk, Prometheus, Grafana, NVIDIA H100/H200/B200/B300, AMD Instinct, NVLink, InfiniBand, NCCL
Responsibilities
Architect control-plane services and APIs for multi-cluster lifecycle and GPU quota enforcement; Design GPU capacity scheduling logic for training vs. inference; Build automated capacity-intake and request-routing tooling; Develop automated remediation for node/workload failures; Scale Kubernetes-based platforms; Lead design reviews and mentor engineers; Drive IaC, GitOps, and CI/CD automation; Participate in on-call and incident response.
Seniority
Senior, hands-on IC with technical leadership
