Machine Learning & AI Infrastructure Engineer

Kforce Inc; Austin (TX); On-site; USD 175,000 - 200,000; Full time

Benefits offered by this job

401(k)

Medical, dental, vision behavior

Job summary

Kforce Inc. is seeking a Machine Learning & AI Infrastructure Engineer in a 100% remote role within the United States. The role blends HPC administration, Kubernetes operations, and AI infrastructure support to run production-grade AI and HPC environments.

You will manage large-scale compute resources, automate workflows, and partner with engineering teams to optimize platforms. Ideal candidates will have hands-on Linux (Ubuntu), Bash/Python scripting, and strong troubleshooting abilities across

Qualifications

• Strong experience administering HPC environments.
• Hands-on Kubernetes administration in on-prem environments.
• Experience with AI cluster administration and infra operations.

Responsibilities

• Administer and support AI and HPC cluster environments.
• Operate day-to-day compute infrastructure at scale.
• Deploy, maintain, and troubleshoot Kubernetes-based platforms.
• Ensure reliability, performance and scalability of compute, storage, and networking.
• Support AI model training and inference infrastructure.
• Automate operations with scripting and tooling.
• Collaborate with engineering and customers to optimize platform.
• Troubleshoot complex infra, networking, storage, and containers.

Skills

HPC administration

Kubernetes administration

AI infrastructure

Linux administration

Bash scripting

Python scripting

Troubleshooting

Tools

NVIDIA BCM

Bright Cluster Manager

MLOps platforms

Kubernetes CSI

Job description

Responsibilities

Kforce has a client in Austin, TX that is seeking a Machine Learning & AI Infrastructure Engineer. This is not a traditional AI Engineer or Data Scientist role. The hiring team is specifically seeking a unique blend of: HPC Administrator + Kubernetes Administrator + AI Infrastructure Operations Engineer. Candidates who have owned, operated, supported, and troubleshot production AI or HPC environments will be the strongest fit. Experience administering and maintaining systems is significantly more important than architecture-only experience. Responsibilities:

• Administer and support AI and HPC cluster environments
• Manage day-to-day operations of large-scale compute infrastructure
• Deploy, maintain, and troubleshoot Kubernetes-based platforms
• Ensure reliability, performance, and scalability across compute, storage, and networking environments
• Support AI model training and inference infrastructure
• Automate operational processes through scripting and tooling
• Partner with engineering teams and customers to optimize platform performance
• Troubleshoot complex infrastructure, networking, storage, and containerization issues
• Support both internal platforms and customer-facing environments

Why Consider This Opportunity?

• 100% Remote Environment
• Exposure to cutting-edge AI, GenAI, and HPC technologies
• Flat organizational structure with minimal bureaucracy
• Direct impact on strategic technology initiatives
• Opportunity to work on platforms that support healthcare, research, drug discovery, and other meaningful AI-driven innovations
• High visibility and collaboration with industry-leading technical teams

Compensation & Benefits:

• Base Salary: $175,000 - $200,000+
• Annual Bonus: Typically 10%-15%
• Medical, Dental, and Vision Coverage
• 401(k)
• Additional performance-based incentives

Requirements

• Strong experience administering High Performance Computing (HPC) environments
• Experience with AI cluster administration and infrastructure operations
• Hands-on Kubernetes administration experience in on-premises environments
• Experience provisioning and managing PV/PVC storage through Kubernetes CSI drivers
• Strong Linux administration skills, specifically Ubuntu
• Scripting experience with Bash and/or Python
• Proven troubleshooting and operational support experience
• Ability to manage and maintain production infrastructure environments

Experience With One Or More Of The Following

• Dell PowerScale/Isilon
• VAST Storage
• NetApp ONTAP
• DDN IntelliFlash
• DDN Exascaler
• Lustre Parallel File Systems

Successful Candidates May Come From Organizations Focused On

• AI Infrastructure
• Machine Learning Platforms
• HPC Operations
• Research Computing
• Biotechnology
• Academic Medical Centers
• Digital Biology
• Financial Services AI Platforms
• Automotive AI Initiatives
• Large-Scale Data Science Environments

Preferred

• NVIDIA ecosystem experience
• NVIDIA Base Command Manager (BCM)
• Bright Cluster Manager
• MLOps platform exposure
• Containerization technologies and orchestration platforms
• High-performance networking experience
• RDMA technologies
• InfiniBand networking
• NVIDIA UFM
• Parallel file system administration
• Storage Technologies (highly desired)

The pay range is the lowest to highest compensation we reasonably in good faith believe we would pay at posting for this role. We may ultimately pay more or less than this range. Employee pay is based on factors like relevant education, qualifications, certifications, experience, skills, seniority, location, performance, union contract and business needs. This range may be modified in the future.

We offer comprehensive benefits including medical/dental/vision insurance, HSA, FSA, 401(k), and life, disability & ADD insurance to eligible employees. Salaried personnel receive paid time off. Hourly employees are not eligible for paid time off unless required by law. Hourly employees on a Service Contract Act project are eligible for paid sick leave.

Note: Pay is not considered compensation until it is earned, vested and determinable. The amount and availability of any compensation remains in Kforce's sole discretion unless and until paid and may be modified in its discretion consistent with the law.

This job is not eligible for bonuses, incentives or commissions.

Kforce is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, pregnancy, sexual orientation, gender identity, national origin, age, protected veteran status, or disability status.