481 Administration jobs in Piedmont

Overview

We are seeking a highly skilled HPC/AI/ML Cluster Engineer to support the design, deployment, and ongoing operations of large-scale HPC environments powered by Slurm. This role centers on cluster engineering, administration, and performance optimization, with emphasis on GPU-accelerated computing, advanced networking, and workload scheduling. In this role, you will work closely with our researchers, vendors, and partners to manage Slurm clusters that are used for AI/ML workloads.

Responsibilities

Cluster Engineering & Deployment

• Participate in the design and bring-up of bare metal HPC/AI/ML environments
• Architect compute node definitions (NUMA, GRES GPU topologies, CPU pinning) and Slurm partitioning strategies for diverse workloads.
• Integrate heterogeneous hardware platforms into cohesive scheduling environments.
• Develop provisioning and imaging workflows (Ansible, MAAS, cloud-init, CI/CD pipelines) for reproducible cluster build-out.
• Coordinate communications between vendors, researchers, and other partners during cluster bring-up and operation.

Slurm Management

• Configure and operate the Slurm Workload Manager.
• Build custom Slurm plugins and scripts (epilog/prolog, pam_slurm_adopt) to extend functionality and integrate with authentication, and monitoring.
• Manage federated Slurm setups across multi-site or hybrid cloud environments.

System Administration & Monitoring

• Administer Linux HPC environments, including network configuration, storage integration, and kernel tuning for HPC workloads.
• Deploy and maintain observability stacks for system health, GPU metrics, and job monitoring.
• Automate failure detection, node health checks, and job cleanup to ensure high uptime and reliability.
• Manage security and access control (LDAP/SSSD, VPN, PAM, SSH session auditing).

User & Stakeholder Support

• Assist cluster users with developing workflows that make efficient use of compute resources.
• Containerize HPC applications with Docker/Podman/Enroot-Pyxis and integrate GPU-aware runtimes into Slurm jobs.
• Automate cost accounting and cluster usage reporting.

Qualifications

• 7+ years experience in HPC cluster administration and engineering, with deep knowledge of Slurm.
• Familiarity with common AI/ML software package dependencies and workflows
• Expert in Slurm configuration, partition design, QoS/preemption policies, and GRES GPU scheduling.
• Strong background in Linux system administration, networking, and performance tuning for HPC environments.
• Hands-on experience with parallel file system, advanced networking (InfiniBand, RoCE, 100/200 GbE), and monitoring stacks.
• Proficient with automation tools (Ansible, Terraform, CI/CD pipelines) and version control.
• Demonstrated ability to operate GPU-accelerated clusters at scale.

Overview

We are seeking a highly skilled HPC/AI/ML Cluster Engineer to support the design, deployment, and ongoing operations of large-scale HPC environments powered by Slurm. This role centers on cluster engineering, administration, and performance optimization, with emphasis on GPU-accelerated computing, advanced networking, and workload scheduling. In this role, you will work closely with our researchers, vendors, and partners to manage Slurm clusters that are used for AI/ML workloads.

Responsibilities

Cluster Engineering & Deployment

• Participate in the design and bring-up of bare metal HPC/AI/ML environments
• Architect compute node definitions (NUMA, GRES GPU topologies, CPU pinning) and Slurm partitioning strategies for diverse workloads.
• Integrate heterogeneous hardware platforms into cohesive scheduling environments.
• Develop provisioning and imaging workflows (Ansible, MAAS, cloud-init, CI/CD pipelines) for reproducible cluster build-out.
• Coordinate communications between vendors, researchers, and other partners during cluster bring-up and operation.

Slurm Management

• Configure and operate the Slurm Workload Manager.
• Build custom Slurm plugins and scripts (epilog/prolog, pam_slurm_adopt) to extend functionality and integrate with authentication, and monitoring.
• Manage federated Slurm setups across multi-site or hybrid cloud environments.

System Administration & Monitoring

• Administer Linux HPC environments, including network configuration, storage integration, and kernel tuning for HPC workloads.
• Deploy and maintain observability stacks for system health, GPU metrics, and job monitoring.
• Automate failure detection, node health checks, and job cleanup to ensure high uptime and reliability.
• Manage security and access control (LDAP/SSSD, VPN, PAM, SSH session auditing).

User & Stakeholder Support

• Assist cluster users with developing workflows that make efficient use of compute resources.
• Containerize HPC applications with Docker/Podman/Enroot-Pyxis and integrate GPU-aware runtimes into Slurm jobs.
• Automate cost accounting and cluster usage reporting.

Qualifications

• 7+ years experience in HPC cluster administration and engineering, with deep knowledge of Slurm.
• Familiarity with common AI/ML software package dependencies and workflows
• Expert in Slurm configuration, partition design, QoS/preemption policies, and GRES GPU scheduling.
• Strong background in Linux system administration, networking, and performance tuning for HPC environments.
• Hands-on experience with parallel file system, advanced networking (InfiniBand, RoCE, 100/200 GbE), and monitoring stacks.
• Proficient with automation tools (Ansible, Terraform, CI/CD pipelines) and version control.
• Demonstrated ability to operate GPU-accelerated clusters at scale.

Overview

We are seeking a highly skilled HPC/AI/ML Cluster Engineer to support the design, deployment, and ongoing operations of large-scale HPC environments powered by Slurm. This role centers on cluster engineering, administration, and performance optimization, with emphasis on GPU-accelerated computing, advanced networking, and workload scheduling. In this role, you will work closely with our researchers, vendors, and partners to manage Slurm clusters that are used for AI/ML workloads.

Responsibilities

Cluster Engineering & Deployment

• Participate in the design and bring-up of bare metal HPC/AI/ML environments
• Architect compute node definitions (NUMA, GRES GPU topologies, CPU pinning) and Slurm partitioning strategies for diverse workloads.
• Integrate heterogeneous hardware platforms into cohesive scheduling environments.
• Develop provisioning and imaging workflows (Ansible, MAAS, cloud-init, CI/CD pipelines) for reproducible cluster build-out.
• Coordinate communications between vendors, researchers, and other partners during cluster bring-up and operation.

Slurm Management

• Configure and operate the Slurm Workload Manager.
• Build custom Slurm plugins and scripts (epilog/prolog, pam_slurm_adopt) to extend functionality and integrate with authentication, and monitoring.
• Manage federated Slurm setups across multi-site or hybrid cloud environments.

System Administration & Monitoring

• Administer Linux HPC environments, including network configuration, storage integration, and kernel tuning for HPC workloads.
• Deploy and maintain observability stacks for system health, GPU metrics, and job monitoring.
• Automate failure detection, node health checks, and job cleanup to ensure high uptime and reliability.
• Manage security and access control (LDAP/SSSD, VPN, PAM, SSH session auditing).

User & Stakeholder Support

• Assist cluster users with developing workflows that make efficient use of compute resources.
• Containerize HPC applications with Docker/Podman/Enroot-Pyxis and integrate GPU-aware runtimes into Slurm jobs.
• Automate cost accounting and cluster usage reporting.

Qualifications

• 7+ years experience in HPC cluster administration and engineering, with deep knowledge of Slurm.
• Familiarity with common AI/ML software package dependencies and workflows
• Expert in Slurm configuration, partition design, QoS/preemption policies, and GRES GPU scheduling.
• Strong background in Linux system administration, networking, and performance tuning for HPC environments.
• Hands-on experience with parallel file system, advanced networking (InfiniBand, RoCE, 100/200 GbE), and monitoring stacks.
• Proficient with automation tools (Ansible, Terraform, CI/CD pipelines) and version control.
• Demonstrated ability to operate GPU-accelerated clusters at scale.

Overview

We are seeking a highly skilled HPC/AI/ML Cluster Engineer to support the design, deployment, and ongoing operations of large-scale HPC environments powered by Slurm. This role centers on cluster engineering, administration, and performance optimization, with emphasis on GPU-accelerated computing, advanced networking, and workload scheduling. In this role, you will work closely with our researchers, vendors, and partners to manage Slurm clusters that are used for AI/ML workloads.

Responsibilities

Cluster Engineering & Deployment

• Participate in the design and bring-up of bare metal HPC/AI/ML environments
• Architect compute node definitions (NUMA, GRES GPU topologies, CPU pinning) and Slurm partitioning strategies for diverse workloads.
• Integrate heterogeneous hardware platforms into cohesive scheduling environments.
• Develop provisioning and imaging workflows (Ansible, MAAS, cloud-init, CI/CD pipelines) for reproducible cluster build-out.
• Coordinate communications between vendors, researchers, and other partners during cluster bring-up and operation.

Slurm Management

• Configure and operate the Slurm Workload Manager.
• Build custom Slurm plugins and scripts (epilog/prolog, pam_slurm_adopt) to extend functionality and integrate with authentication, and monitoring.
• Manage federated Slurm setups across multi-site or hybrid cloud environments.

System Administration & Monitoring

• Administer Linux HPC environments, including network configuration, storage integration, and kernel tuning for HPC workloads.
• Deploy and maintain observability stacks for system health, GPU metrics, and job monitoring.
• Automate failure detection, node health checks, and job cleanup to ensure high uptime and reliability.
• Manage security and access control (LDAP/SSSD, VPN, PAM, SSH session auditing).

User & Stakeholder Support

• Assist cluster users with developing workflows that make efficient use of compute resources.
• Containerize HPC applications with Docker/Podman/Enroot-Pyxis and integrate GPU-aware runtimes into Slurm jobs.
• Automate cost accounting and cluster usage reporting.

Qualifications

• 7+ years experience in HPC cluster administration and engineering, with deep knowledge of Slurm.
• Familiarity with common AI/ML software package dependencies and workflows
• Expert in Slurm configuration, partition design, QoS/preemption policies, and GRES GPU scheduling.
• Strong background in Linux system administration, networking, and performance tuning for HPC environments.
• Hands-on experience with parallel file system, advanced networking (InfiniBand, RoCE, 100/200 GbE), and monitoring stacks.
• Proficient with automation tools (Ansible, Terraform, CI/CD pipelines) and version control.
• Demonstrated ability to operate GPU-accelerated clusters at scale.

Overview

We are seeking a highly skilled HPC/AI/ML Cluster Engineer to support the design, deployment, and ongoing operations of large-scale HPC environments powered by Slurm. This role centers on cluster engineering, administration, and performance optimization, with emphasis on GPU-accelerated computing, advanced networking, and workload scheduling. In this role, you will work closely with our researchers, vendors, and partners to manage Slurm clusters that are used for AI/ML workloads.

Responsibilities

Cluster Engineering & Deployment

• Participate in the design and bring-up of bare metal HPC/AI/ML environments
• Architect compute node definitions (NUMA, GRES GPU topologies, CPU pinning) and Slurm partitioning strategies for diverse workloads.
• Integrate heterogeneous hardware platforms into cohesive scheduling environments.
• Develop provisioning and imaging workflows (Ansible, MAAS, cloud-init, CI/CD pipelines) for reproducible cluster build-out.
• Coordinate communications between vendors, researchers, and other partners during cluster bring-up and operation.

Slurm Management

• Configure and operate the Slurm Workload Manager.
• Build custom Slurm plugins and scripts (epilog/prolog, pam_slurm_adopt) to extend functionality and integrate with authentication, and monitoring.
• Manage federated Slurm setups across multi-site or hybrid cloud environments.

System Administration & Monitoring

• Administer Linux HPC environments, including network configuration, storage integration, and kernel tuning for HPC workloads.
• Deploy and maintain observability stacks for system health, GPU metrics, and job monitoring.
• Automate failure detection, node health checks, and job cleanup to ensure high uptime and reliability.
• Manage security and access control (LDAP/SSSD, VPN, PAM, SSH session auditing).

User & Stakeholder Support

• Assist cluster users with developing workflows that make efficient use of compute resources.
• Containerize HPC applications with Docker/Podman/Enroot-Pyxis and integrate GPU-aware runtimes into Slurm jobs.
• Automate cost accounting and cluster usage reporting.

Qualifications

• 7+ years experience in HPC cluster administration and engineering, with deep knowledge of Slurm.
• Familiarity with common AI/ML software package dependencies and workflows
• Expert in Slurm configuration, partition design, QoS/preemption policies, and GRES GPU scheduling.
• Strong background in Linux system administration, networking, and performance tuning for HPC environments.
• Hands-on experience with parallel file system, advanced networking (InfiniBand, RoCE, 100/200 GbE), and monitoring stacks.
• Proficient with automation tools (Ansible, Terraform, CI/CD pipelines) and version control.
• Demonstrated ability to operate GPU-accelerated clusters at scale.

• Administrative Excellence - Handle daily benefits administration tasks, including filing, data entry, scanning, organizing files, and assembling benefits materials, presentations, and communications.
• Data & Reporting - Run HR system reports, maintain records, and update files to ensure accuracy and compliance with benefit plan requirements and deadlines.
• Invoice & Payment Coordination - Audit, reconcile, and process benefit-related invoices; manage retroactive changes, charges, and refunds; and research and resolve billing discrepancies.
• Leave of Absence Support - Maintain LOA case records, track documentation, prepare required notices, and generate correspondence to ensure a smooth leave process for employees.
• Compliance & Accuracy - Ensure all processes meet applicable plan rules, restrictions, and timelines while safeguarding sensitive information in accordance with HIPAA protocols.

• Education - High school diploma or equivalent required.
• Experience -

• 2+ years in benefits administration and invoice reconciliation.
• Experience with benefit/insurance brokers preferred.

• Skills & Knowledge -

• Familiarity with benefit program regulations and leave management practices.
• Strong analytical, math, and process management skills.
• Proficiency in HRIS or benefits/leave management software.
• Microsoft Office: Intermediate Excel; basic Word and Outlook skills.
• Ability to handle confidential information with discretion and accuracy.
• Familiarity with UKG Pro and PlanSource preferred.

UC Riverside's Auxiliary Services is recruiting for the APPS Workforce Administration (WFA) Analyst. The full salary range for the APPS Workforce Administration (WFA) Analyst is $27.63 - $7.56 per hour. However, the expected pay scale for this position is up to 37.60 per hour. We base salary offers on a variety of considerations, such as education, licensure and certifications, experience, and other business and organizational needs.

The Auxiliary Payroll & Personnel Services (APPS) unit provides payroll and personnel related services including recruitment, onboarding, offboarding, time reporting, payroll oversight, position management, personnel updates, case management (benefits, leave balances, accruals, etc.) and leave processing for Auxiliary Services. Reporting to the APPS Manager, the APPS Workforce Administration (WFA) Analyst will work with a wide range of clients to gather information that needs to be processed from their respective departments, and ensure accurate entry and handling of information related to the requests for services in order to minimize errors in the process. This position will be responsible for providing project management support to create, organize and execute upcoming mass onboarding/offboarding/payroll related requests, will be responsible for timely and accurate review, preparation, processing, and auditing of payroll, personnel, and financial transactions, and will utilize data and analytics to complete audits, identify trends in delayed/inaccurate processing. Interacts with client partners and colleagues in UCR's Central Office, the Campus Service Center, and the UCPath Center to resolve service escalation issues. Is the first point of contact for department partners for questions concerning employment appointments. The incumbent will partner with the APPS Manager, APPS team, other Shared Service Centers, clients, and stakeholders to identify opportunities to continuously improve the effectiveness, accuracy, and delivery of services.

Applicants must have current work authorization when accepting a UCR staff position. Currently, we are unable to sponsor or take over sponsorship of an employment Visa for staff.

As a University employee, you will be required to comply with all applicable University policies and/or collective bargaining agreements, as may be amended from time to time. Federal, state, or local government directives may impose additional requirements.

Year Up United is a one-year or less, intensive job training program that provides young adults with in-classroom skill development, access to internships and/or job placement services, and personalized coaching and mentorship. Year Up United participants also receive an educational stipend.

The program combines technical and professional training with access to internships and job placement support through our industry-leading talent placement firm YUPRO Placement. If you receive an internship, it may be at Salesforce, Workday, or PayPal among other leading organizations in the California Bay Area (Pleasant Hill, San Francisco, San Jose).

Are you eligible?
You can apply to Year Up United if you are:
- A high school graduate or GED recipient
- Eligible to work in the U. S.
- Available Monday-Friday throughout the duration of the program
- Highly motivated to learn technical and professional skills
- Have not obtained a Bachelor s degree
- You may be required to answer additional screening questions when applying

What will you gain?
Professional business and communication skills, interviewing and networking skills, resume building, ongoing support and guidance to help you launch your career. During the internship phase, Year Up United students earn an educational stipend of $525 per week.

In-depth classes include:
- Application Development
- Customer Success
- Project Management
- Data Analytics
- IT Support
- Business Operations
- Network Security & Support

Get the skills and opportunity you need to launch your professional career.
75% of Year Up United graduates are employed and/or enrolled in postsecondary education within 4 months of graduation. Employed graduates earn an average starting salary of fifty-three thousand dollars per year.

Year Up United is a one-year or less, intensive job training program that provides young adults with in-classroom skill development, access to internships and/or job placement services, and personalized coaching and mentorship. Year Up United participants also receive an educational stipend.

The program combines technical and professional training with access to internships and job placement support through our industry-leading talent placement firm YUPRO Placement. If you receive an internship, it may be at Salesforce, Workday, or PayPal among other leading organizations in the California Bay Area (Pleasant Hill, San Francisco, San Jose).

Are you eligible?
You can apply to Year Up United if you are:
- A high school graduate or GED recipient
- Eligible to work in the U. S.
- Available Monday-Friday throughout the duration of the program
- Highly motivated to learn technical and professional skills
- Have not obtained a Bachelor s degree
- You may be required to answer additional screening questions when applying

What will you gain?
Professional business and communication skills, interviewing and networking skills, resume building, ongoing support and guidance to help you launch your career. During the internship phase, Year Up United students earn an educational stipend of $525 per week.

In-depth classes include:
- Application Development
- Customer Success
- Project Management
- Data Analytics
- IT Support
- Business Operations
- Network Security & Support

Get the skills and opportunity you need to launch your professional career.
75% of Year Up United graduates are employed and/or enrolled in postsecondary education within 4 months of graduation. Employed graduates earn an average starting salary of fifty-three thousand dollars per year.