Teams at Submer

Design, build, and operate large-scale, low-latency telemetry pipelines and observability systems for GPU cloud and edge infrastructure. Instrument compute, storage, networking, and AI workloads; implement metrics, logging, tracing, SLOs, alerting, dashboards, anomaly detection, and integrate telemetry into operational workflows. Lead observability initiatives, collaborate with platform teams, and support on-call responsibilities.

Hands-on engineer responsible for deploying, validating, and operating GPU cloud infrastructure in datacenters. Duties include rack-and-stack, cabling and optics validation, BIOS/firmware and GPU/DPU bring-up, network and storage integration, platform stack installation, acceptance testing, runbook creation, Day-2 maintenance, observability validation, and cross-team coordination with vendors and engineering for production readiness.

Design, build, and operate the AI storage layer for GPU-heavy edge and core deployments. Architect and optimize storage for distributed training and inference, integrate storage with Kubernetes (CSI), tune performance (RDMA, NVMe-oF, GPU Direct Storage), lead reliability and operational practices, and provide staff-level architectural ownership and cross-team influence while executing hands-on storage engineering.