Sr. Staff Observability Engineer (GPU Cloud & Telemetry Platform)
Core
Design and evolve a planet-scale observability platform for GPU-as-a-Service infrastructure, enabling deep insights into GPU clusters, datacenter systems, and distributed ML workloads.
Role type
Sr. Staff Observability Engineer (GPU Cloud & Telemetry Platform)
Builds
Production telemetry pipelines (metrics/logs/traces) and dashboards for GPUaaS infrastructure
Domain
Cloud Infrastructure / GPU Computing / Observability
Deliverable
production ML models | infrastructure
Required skills
Go, Python, Kubernetes, Linux internals, NVIDIA DCGM, CUDA ecosystem, high-performance networking (RDMA, InfiniBand), time-series databases, log storage systems, SRE principles, CI/CD automation, Terraform, OpenTelemetry
Preferred skills
Experience with GPU hardware (MIG, NVLink, PCIe), predictive observability, Zero Trust patterns, multi-tenant isolation
Technologies
Grafana Alloy, Mimir, Loki, Vector, Prometheus, Datadog, Terraform, Kubernetes, OpenTelemetry
Responsibilities
Architect low-latency, high-throughput telemetry pipelines for GPU metrics and logs; Define GPU-specific SLIs/SLOs and SLO-driven observability strategies; Build rich Grafana dashboards for fleet health and capacity planning; Lead incident forensics and cross-layer debugging for GPU contention and performance issues; Mentor engineers and drive adoption of Observability-by-Design across teams
Seniority
Sr. Staff, strategic architecture & hands-on engineering