Summary
Malomatia is hiring a Consultant for operations oversight and performance across AI infrastructure. The role oversees post-go-live delivery of GPU infrastructure and its Kubernetes runtime, monitors KPIs and SLAs, and drives service improvements with third-party providers. Responsibilities include reviewing GPU scheduling, workloads, observability, capacity and maintenance plans, and operational risks. Applicants should have 10 years of relevant GPU or HPC operations or service-management experience and at least 7 years with Kubernetes; CKA and NVIDIA AI infrastructure certifications are preferred.
The posting
As published on malomatia.com. Pulled from the employer's site and shown as they wrote it.
The Consultant – Operations Oversight & Performance, AI Infrastructure is responsible for Oversee OEM ongoing operational delivery after go-live. Ensure the GPU infrastructure AI Runtime Layer - Kubernetes, GPU scheduling, container runtime, workloads, and autoscaling are operated to agreed performance standards and drive continuous improvement through structured oversight.
Responsibilities
Define, agree, and monitor operational KPIs and SLAs with 3rd party (availability, incident response, resolution times, change success rate, capacity utilization, etc.).
Escort Operation and hardening of Kubernetes clusters with GPU Operator, device plugins, DRA, MIG/time-slicing, and advanced schedulers (Kueue or equivalents).
Review GPU-aware scheduling, fair-share/quotas, priority classes, preemption, and multi-tenancy isolation.
Supervise manages container runtime, AI workloads (training/inference), and autoscaling.
Review integrate observability (Prometheus/Grafana + DCGM), logging, and GitOps for the runtime layer.
Support multi-cluster federation and cluster lifecycle (in partnership with Rafay layer).
Conduct regular operational reviews of Advanced NOC performance, incident trends, problem management, and change records.
Drive service improvement plans and hold 3rd party accountable for operational performance.
Review capacity, lifecycle, and maintenance plans; escalate risks to the Program Delivery Lead.
Ensure operational processes support future Platform foundation requirements (observability, identity, scheduling readiness).
Coordinate planned works, maintenance windows, and operational communications with internal stakeholders.
Maintain the operational risk register and support audit/compliance evidence collection.
Qualifications
Required Experience & Background:
10 years in GPU and HPC infrastructure operations, service management, or managed-service oversight roles.
7+ years Kubernetes (CKA preferred); deep experience running GPU workloads at scale.
Strong knowledge of CNCF ecosystem, operators, CRDs, and GPU-specific features (NVIDIA GPU Operator, DRA).
Excellent understanding of GPU or high-performance compute operations, observability, and incident/change management.
Strong analytical, reporting, and stakeholder management skills.
Preferred Certifications:
NCP-AII – NVIDIA-Certified Professional: AI Infrastructure
NCP-AIO – NVIDIA-Certified Professional: AI Operations
NCP-AIN – NVIDIA-Certified Professional: AI Networking
Red Hat Certified Specialist in Containers and Kubernetes – OpenShift Container Platform 4.6
Red Hat Certified Specialist in OpenShift Administration
Any service management or performance management credentials – advantageous
Relevant Linux or systems certifications (RHCSA or equivalent) – advantageous