Kubernetes & HPC Infrastructure Engineer

Company Description SARACA is a global engineering R&D services company supporting more than 25 Fortune 500 customers across MedTech, aerospace, rail, automotive, semiconductor, defense, and farm equipment industries. The organization is ISO 13485 certified and has deep expertise in medical device design and development, including embedded software, UI/UX, mechanical systems, and product testing. SARACA’s team of 400+ engineers and consultants delivers complex product engineering projects both onsite and offsite, backed by strong knowledge in IEC 62304, EU MDR, and scientific and regulatory documentation. With a global presence, SARACA focuses on solving challenging business problems and accelerating customer growth while promoting a culture of innovation, continuous learning, and equal opportunity.
Role: Kubernetes & HPC Infrastructure Engineer
Location: USA – Remote
Start Date: Immediate
Background Check: Mandatory
Job Summary
We are seeking a hands-on Kubernetes & HPC Infrastructure Engineer to design, deploy, manage, and optimize large-scale cloud-native, HPC, and GPU compute environments. The ideal candidate will have strong experience with Kubernetes, Linux, containerization, HPC clusters, GPU infrastructure, workload schedulers, automation, and cloud platforms.
Key Responsibilities
Design, deploy, and manage scalable Kubernetes and HPC compute platforms.
Support AI/ML, engineering simulation, scientific computing, and data-intensive workloads.
Deploy and manage Kubernetes workloads using Docker, Helm, and container orchestration technologies.
Administer HPC clusters and manage workload schedulers such as Slurm and Volcano.
Manage and optimize NVIDIA GPU infrastructure for AI/ML and high-performance workloads.
Administer Linux-based infrastructure and automate operational tasks using Python and Bash.
Implement and maintain CI/CD pipelines, monitoring, infrastructure automation, and cloud-native solutions.
Troubleshoot complex issues across Kubernetes, HPC, GPU, Linux, networking, and distributed compute environments.
Perform performance tuning and optimization of large-scale distributed compute platforms.
Required Qualifications & Skills
5+ years of experience in Kubernetes, cloud infrastructure, or platform engineering.
2+ years of hands-on experience with HPC or large-scale compute environments.
Strong hands-on experience with Kubernetes, Docker, Helm, and Linux.
Experience with HPC workload schedulers such as Slurm, Volcano, or similar technologies.
Strong knowledge of GPU infrastructure, preferably NVIDIA, and AI/ML workloads.
Strong Linux administration and troubleshooting skills.
Proficiency in Python and/or Bash scripting.
Experience with CI/CD, monitoring, infrastructure automation, and DevOps practices.
Experience with at least one major cloud platform: AWS EKS, Azure AKS, or GCP GKE.
Preferred Skills
Experience with RDMA / InfiniBand and high-speed networking.
Experience with parallel/distributed storage systems.
Experience managing large-scale GPU/HPC environments.
Experience supporting engineering simulations, semiconductor workloads, AI model training, or scientific computing.
Knowledge of distributed computing and performance optimization.

Work arrangement
Yes