Senior HPC Engineer for Quantum Platform - Hybrid

Clutch Canada; Maryland; Hybrid; USD 146,000 - 209,000; Full time

Benefits offered by this job

Hybrid work model

Remote work a few days per week

Job summary

IonQ, Inc. in College Park, MD, is seeking an HPC Cluster Engineer to build and operate the internal HPC platform used by researchers and application developers to advance quantum computing. You will design, deploy, and maintain the hybrid on-prem and cloud infrastructure.

The role emphasizes automation, scale, and collaboration with the Infrastructure Team, plus opportunities to work with NVIDIA GPUs and modern HPC schedulers.

Qualifications

• 5+ years of Linux HPC experience with cluster management and tuning.
• Familiarity with Slurm, PBS, or Grid Engine schedulers.
• Proficiency with Python, Go, and Bash scripting.

Responsibilities

• Design, deploy, and operate HPC systems for quantum simulations and applications.
• Develop automation and tooling for configuring Linux systems on‑prem and in the cloud.
• Support researchers and developers running simulations and workloads.
• Build technical relationships with stakeholders across teams and workloads.
• Self-manage projects, priorities, and deadlines; identify and mitigate risks.
• Grow into a go‑to resource for HPC configuration within IonQ's tech community.

Skills

Linux systems

HPC clusters

Scripting

Python

Go

Bash

Git

Ansible

Automation tooling

Education

Bachelor's degree in computer science, engineering, or equivalent

Tools

Slurm

PBS

Grid Engine

Docker

Kubernetes

NVIDIA GPUs

InfiniBand

RoCE

Podman

Singularity

Enroot

GCP

AWS

Git

Job description

IonQ, Inc. in College Park, MD, is seeking an HPC Cluster Engineer to build and operate the internal HPC platform used by researchers and application developers to advance quantum computing. You will design, deploy, and maintain the hybrid on-prem and cloud infrastructure.

The role emphasizes automation, scale, and collaboration with the Infrastructure Team, plus opportunities to work with NVIDIA GPUs and modern HPC schedulers.