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Hpc On Azure Jobs (NOW HIRING)

AI/HPC System Engineer

San Jose, CA · On-site

$80 - $90/hr

Hands-on experience with Linux-based infrastructure and public cloud environments such as AWS, Azure, or GCP * Experience deploying or operating GPU/HPC environments, including workload scheduling or ...

Hands-on experience with Linux-based infrastructure and public cloud platforms such as AWS, Azure, or GCP. * Experience deploying, configuring, or operating GPU and/or HPC environments. * Experience ...

Keylent Inc is seeking an experienced HPC Consultant to provide support for users in the India/Asia ... and hands on with Cloud technologies: Prefer using Azure and Terraform for VM creations and ...

HPC-Kubernetes Solutions Architect

Dallas, TX · On-site

$62.25 - $82.25/hr

... on-premise environments. • Provide architectural leadership during onboarding and deployment ... or Azure Solutions Architect Expert. Company : INSPYR Solutions is a information technology ...

US Tech Solutions is a global staff augmentation firm providing a wide range of talent on-demand ... Azure public clouds. Able to provision and manage instances, build images, write installation ...

Hands-on experience with Linux-based infrastructure and public cloud platforms such as AWS, Azure, or GCP. Experience deploying, configuring, or operating GPU and/or HPC environments. Experience with ...

At Rescale, this means you will work on and impact: * Become an expert in the Rescale platform and ... Familiarity with cloud computing platforms such as AWS, Azure or Google Cloud * High-level ...

$61K - $141K/yr

Experience with HPC systems and on-prem or HPC administration * Experience developing enterprise cloud-native solutions involving Kubernetes, Docker, AWS, Jenkins, or Azure * Experience writing ...

DevOps HPC Engineer

Atlanta, GA · On-site

$61K - $141K/yr

Experience with HPC systems and on-prem or HPC administration * Experience developing enterprise cloud-native solutions involving Kubernetes, Docker, AWS, Jenkins, or Azure * Experience writing ...

DevOps HPC Engineer

Atlanta, GA · On-site

$61K - $141K/yr

Experience with HPC systems and on-prem or HPC administration * Experience developing enterprise cloud-native solutions involving Kubernetes, Docker, AWS, Jenkins, or Azure * Experience writing ...

DevOps HPC Engineer

Atlanta, GA · On-site

$61K - $141K/yr

Experience with HPC systems and on-prem or HPC administration * Experience developing enterprise cloud-native solutions involving Kubernetes, Docker, AWS, Jenkins, or Azure * Experience writing ...

DevOps HPC Engineer

Washington, DC · On-site

$61K - $141K/yr

Experience with HPC systems and on-prem or HPC administration * Experience developing enterprise cloud-native solutions involving Kubernetes, Docker, AWS, Jenkins, or Azure * Experience writing ...

DevOps HPC Engineer

Atlanta, GA · On-site

$61K - $141K/yr

Experience with HPC systems and on-prem or HPC administration * Experience developing enterprise cloud-native solutions involving Kubernetes, Docker, AWS, Jenkins, or Azure * Experience writing ...

Showing results 21-40

Hpc On Azure information

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How much do hpc on azure jobs pay per hour?

As of Sep 13, 2026, the average hourly pay for hpc on azure in the United States is $58.40, according to ZipRecruiter salary data. Most workers in this role earn between $52.88 and $65.62 per hour, depending on experience, location, and employer.

What is HPC on Azure?

HPC on Azure refers to High Performance Computing solutions that leverage Microsoft Azure's cloud infrastructure to run complex and large-scale computational workloads. Organizations use Azure's scalable computing resources to perform simulations, data analysis, scientific research, and engineering tasks without the need to maintain expensive on-premises hardware. Azure offers specialized virtual machines, fast networking, and integrated storage to support demanding HPC applications. This allows users to scale resources as needed and only pay for what they use, making high-performance computing more accessible and cost-effective.

What are some typical challenges faced when managing HPC workloads on Azure, and how can they be addressed?

Professionals managing HPC workloads on Azure often encounter challenges related to optimizing resource allocation, managing job scheduling, and ensuring high performance across scalable cloud infrastructure. Addressing these issues typically involves leveraging Azure-native tools like Azure CycleCloud or Batch for automated provisioning and monitoring, as well as carefully selecting VM types and storage options suited for specific workload demands. Regular collaboration with IT, data science, and engineering teams is crucial to ensure that workflows remain efficient, secure, and cost-effective.

What are the key skills and qualifications needed to thrive as an HPC on Azure specialist, and why are they important?

To thrive as an HPC on Azure specialist, you need a strong background in high-performance computing, cloud architectures, and experience with parallel processing frameworks, often supported by degrees in computer science or engineering. Familiarity with Azure services such as Azure Batch, Azure CycleCloud, and networking/security configurations, as well as certifications like Microsoft Certified: Azure Solutions Architect Expert, are highly valuable. Strong problem-solving skills, communication, and adaptability are essential for collaborating with diverse teams and addressing evolving customer requirements. These skills enable the efficient deployment, scaling, and management of HPC workloads on Azure, ensuring optimal performance and cost-effectiveness.
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Infographic showing various Hpc On Azure job openings in the United States as of September 2026, with employment types broken down into 93% Full Time, 1% Part Time, and 6% Contract. Highlights an 73% Physical, 8% Hybrid, and 19% Remote job distribution, with an average salary of $121,476 per year, or $58.4 per hour.

AI/HPC System Engineer

San Jose, CA • On-site

Xoriant Corporation
IT Services • 1 - 5K employees

Other

Posted 20 days ago


Job description

Position Title: AI/HPC System Engineer

Location: San Jose, CA (Onsite)

Description

We are hiring an AI/HPC System Engineer to build and operate the compute infrastructure supporting our HPC and AI development workloads. This role deploys, automates, and maintains GPU clusters across on-premise and cloud environments, delivering reliable, scalable, and cost-efficient compute for engineering and R&D teams.

Responsibilities:

• GPU/HPC infrastructure: Build, configure, and operate GPU and HPC clusters across compute, storage, and networking; support capacity planning, performance tuning, and optimization for AI training, inference, and compute-intensive workloads

• Hybrid cloud infrastructure: Deploy and maintain compute environments spanning on-premise and public cloud, and contribute to modernization and scaling initiatives for HPC/AI infrastructure

• Automation and observability: Implement infrastructure-as-code, provisioning automation, monitoring, and alerting, and drive improvements in resource utilization and efficiency

• AI platform support: Deploy, integrate, and support LLM APIs, coding assistants, and AI/agent platforms used by internal engineering teams

• Operations and collaboration: Troubleshoot and resolve infrastructure issues, document standards and runbooks, and work with relevant stakeholders to support day-to-day IT operations

Qualifications:

• Bachelor''s degree in Computer Science, Engineering, or a related technical field

• 3+ years of hands-on experience in IT infrastructure, cloud, platform engineering, or HPC

• Hands-on experience with Linux-based infrastructure and public cloud environments such as AWS, Azure, or Google Cloud Platform

• Experience deploying or operating GPU/HPC environments, including workload scheduling or orchestration platforms such as Kubernetes or Slurm

• Experience with infrastructure automation, monitoring, troubleshooting, and performance optimization

• Solid understanding of compute, storage, networking, and container technologies; experience with AI/ML infrastructure or workloads is a plus

• Strong collaboration and communication skills, with the ability to work across engineering and IT teams