Note: The job is a remote job and is open to candidates in USA. KPG99 INC is recruiting for an unnamed client seeking an HPC AI/ML Platform Engineer. The role supports and scales multi-cloud infrastructure for GPU-intensive model training, deep learning research, and production AI workloads, with a focus on Kubernetes, GPU resource allocation, Slurm scheduling, and automation.

Responsibilities

• Engineers on this team will help provision and operate large-scale compute environments, manage Kubernetes-based infrastructure, optimize GPU resource allocation, support Slurm scheduling systems, and build automation that enables rapid AI platform growth
• Provision HPC infrastructure through CI/CD systems across AWS, CoreWeave, GCP, OCI, and additional cloud providers
• Operate and troubleshoot large-scale Kubernetes platforms supporting GPU-intensive workloads
• Define and maintain SLIs/SLOs, monitoring, alerting, incident response, and post-incident reviews
• Partner closely with Networking, Storage, Security, and AI/ML Platform teams

Skills

• USC/GC
• Hands-on experience supporting High Performance Computing (HPC), AI/ML, Deep Learning, or GPU-intensive production environments at enterprise scale
• Candidates should demonstrate experience supporting model training workloads, distributed compute platforms, or large-scale AI infrastructure
• Strong experience operating production Kubernetes platforms supporting high-performance workloads, including cluster lifecycle management, scheduling, networking, upgrades, troubleshooting, and platform reliability
• Experience supporting Slurm or similar workload schedulers used to allocate compute resources across AI model training and inference workloads
• Strong Terraform and Python experience for provisioning, managing, automating, and scaling infrastructure environments
• Proven experience supporting High Performance Computing (HPC) environments at enterprise scale
• Experience supporting AI/ML or Deep Learning infrastructure, including model training workloads
• Provision HPC infrastructure through CI/CD systems across AWS, CoreWeave, GCP, OCI, and additional cloud providers
• Experience managing or supporting Slurm-based job scheduling environments
• Operate and troubleshoot large-scale Kubernetes platforms supporting GPU-intensive workloads
• Define and maintain SLIs/SLOs, monitoring, alerting, incident response, and post-incident reviews
• Experience operating environments where performance, cluster stability, and GPU utilization directly impact business outcomes
• 4+ years supporting HPC, AI/ML Infrastructure, Machine Learning Platforms, or Deep Learning environments
• Strong experience with distributed compute, GPU infrastructure, or large-scale training environments
• Cluster lifecycle management
• Scheduler troubleshooting
• Node pool management
• Networking and CNI troubleshooting
• Production upgrades across large fleets
• Terraform experience building and managing infrastructure through Infrastructure as Code
• Python experience for platform automation and operational tooling
• Working knowledge of AWS services including EC2, S3, EFS, and FSx for Lustre
• Understanding of GPU utilization, workload orchestration, and distributed compute environments is highly desired
• Experience With Slurm Job Scheduling Strongly Preferred
• Experience supporting ML training, inference, deep learning, large language model (LLM), or GPU-intensive workloads preferred

Benefits

• 100% remote

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