HPC / Linux / Cloud Engineer (GPU, Kubernetes, AWS/Azure) – 1 Year Renewable Contract

About the Role

We are seeking motivated HPC / Linux / Cloud Engineers (Lead Engineer) to support and scale high-performance computing (HPC) environments powering advanced analytics, AI/ML, and GPU-intensive workloads.

This role offers a rare opportunity to work across Linux infrastructure, GPU clusters, Kubernetes platforms, and cloud-native environments supporting enterprise-scale compute platforms.

Candidates with strengths in Linux systems, cloud engineering, platform engineering, containers, or HPC environments are encouraged to apply.

Lead Engineer

• 8+ years of relevant experience

Key Responsibilities

• Manage and support Linux-based compute infrastructure and HPC clusters
• Administer CPU/GPU environments for AI/ML and high-performance workloads
• Monitor infrastructure performance, availability, and system health
• Troubleshoot Linux, storage, networking, and cluster-related issues
• Support and optimize workload schedulers such as PBS Professional or Slurm
• Deploy and manage containerized workloads using Docker and Kubernetes
• Support cloud-based HPC deployments across AWS, Azure, or GCP
• Assist AI/ML teams with GPU utilization, workload tuning, and performance optimization
• Automate infrastructure provisioning and configuration using Terraform, Ansible, or similar tools
• Maintain system documentation, SOPs, and operational procedures
• Collaborate with engineering, data science, and infrastructure teams to improve platform reliability and scalability
• Participate in incident response, root cause analysis, and system recovery activities

Required Skills & Experience

• Hands-on Linux administration experience (RHEL/CentOS/Ubuntu or similar)
• Experience supporting infrastructure, cloud, or platform environments
• Exposure to AWS, Azure, or Google Cloud Platform
• Familiarity with containers and orchestration technologies
• Basic scripting or automation experience (Bash, Python, Shell, etc.)
• Understanding of infrastructure monitoring and troubleshooting

Preferred / Good-to-Have Skills

• HPC or cluster computing environments
• Job scheduling platforms such as:PBS ProfessionalSlurm
• Kubernetes, Docker, or Singularity
• GPU computing technologies:NVIDIA CUDAPyTorchTensorFlow
• Infrastructure as Code:TerraformCloudFormationAnsible
• Monitoring and observability tools:GrafanaPrometheusELK Stack
• Experience supporting AI/ML workloads
• Exposure to hybrid cloud infrastructure
• Understanding of networking, storage, and security concepts in HPC environments

Ideal Candidate Profile

You are someone who:

• Enjoys solving infrastructure and performance challenges
• Has strong Linux troubleshooting skills
• Is interested in GPU, AI/ML, or large-scale compute systems
• Can work across cloud, infrastructure, and platform engineering domains
• Is eager to learn and grow within HPC and modern compute environments

We value depth in a few technical areas rather than expecting expertise across every technology listed.

Why Join

• Work on cutting-edge GPU and AI/ML platforms
• Gain exposure to both cloud and HPC technologies — a highly sought-after combination
• Opportunity to work on enterprise-scale compute environments
• Build expertise in modern platform engineering and high-performance infrastructure
• Grow into specialized HPC, Kubernetes, GPU, or cloud engineering roles