HPC Engineer

Overview

Are you passionate about high performance computing, AI infrastructure, AWS, and Linux? If so, this is the environment for you.

Join one of the world’s leading Research companies to help shape the future of research technology. You will be part of a brand new research computing team, driving innovation through high performance computing and AI. This is your chance to design, build, and manage advanced infrastructure that powers world-class research across a wide range of disciplines and tackles real-world challenges. In this role you will help create a high-performance environment that allows researchers to push the boundaries in computational modeling, machine learning, simulations, and analytics.

Your work will directly support projects across multiple domains, from social sciences to computational research, ensuring availability, performance, and security across GPU clusters, high-speed networks, and storage systems. You will also help researchers transition to AWS and work with tools and technologies such as AWS, Linux, Terraform, Ansible, HPC, GPU systems, and Slurm.

Responsibilities

Help create, manage, and optimize a high-performance environment that enables researchers to conduct advanced simulations, machine learning, and analytics on GPU clusters, high-speed networks, and storage systems.

Support the transition of researchers to AWS cloud, leveraging AWS, Linux, Terraform, Ansible, HPC, GPU systems, and scheduling tools like Slurm.

Qualifications

• Hybrid or cloud based HPC solutions such as AWS, Azure, or GCP
• Advanced Linux system administration in research computing environments
• Workload management and scheduling tools such as Slurm, PBS, HTCondor, or Kubernetes
• Scripting and automation using Python, Bash, or Ansible
• Infrastructure as code using Terraform

How to Apply

If this sounds like you and you’re open to hearing more details, apply below or send an email

• Hybrid or cloud based HPC solutions such as AWS, Azure, or GCP
• Advanced Linux system administration in research computing environments
• Workload management and scheduling tools such as Slurm, PBS, HTCondor, or Kubernetes
• Scripting and automation using Python, Bash, or Ansible
• Infrastructure as code using Terraform