GenAI Platform Engineer: Multi-GPU & Kubernetes Lead

Quantiphi; United States; On-site; USD 140,000 - 210,000; Full time

Job summary

Quantiphi seeks a Senior Platform Engineer to design, optimize, and scale GenAI infrastructure. You will lead multi-GPU environments, GPU profiling, and distributed training, partnering with data science, MLOps, and application teams for production deployments.

Ideal candidates have hands-on OpenShift/Kubernetes, NVIDIA GPU stack expertise, and IaC skills. This remote US/Canada role offers growth, collaboration with Fortune 500 clients, and cutting-edge AI workloads.

Qualifications

• Experience with Slurm and distributed training environments.
• Hands-on expertise with Red Hat OpenShift and/or Kubernetes.
• Deep knowledge of the NVIDIA GPU ecosystem (CUDA, cuDNN, NCCL, TensorRT).
• Strong foundation in Linux systems, performance tuning, and multi-GPU optimization.
• Experience deploying GenAI workloads (LLM fine-tuning, RAG pipelines, multi-modal systems).
• Familiarity with Infrastructure-as-Code tools (Terraform, Ansible).
• Experience with cloud GPU environments (GCP, Azure, AWS, OCI) and/or on-prem GPU clusters.
• Experience with NVIDIA NIMs, DGX systems, or GPU-accelerated containers.
• Knowledge of LLMOps frameworks and MLOps integration.
• Familiarity with vector databases and retrieval systems for RAG architectures.

Responsibilities

• Design and implement scalable infrastructure for LLM and GenAI workloads across multi-GPU environments.
• Perform GPU profiling, benchmarking, and performance optimization for distributed training workloads.
• Manage and schedule compute-intensive jobs using Slurm-based clusters and OpenShift/Kubernetes environments.
• Enable and optimize the NVIDIA GPU stack (CUDA, cuDNN, NCCL, Triton, RAPIDS, etc.).
• Collaborate with cross-functional teams to deploy models in research and production environments.
• Build and support GenAI pipelines (fine-tuning, RAG, multi-modal inferencing, LLMOps).
• Develop reusable infrastructure templates using tools like Terraform and Helm.
• Contribute to internal innovation (PoCs, workshops) and support client-facing delivery engagements.

Skills

Slurm distributed training

LLMOps frameworks

MLOps integration

Multi-GPU optimization

Linux performance tuning

Tools

Slurm

OpenShift

Kubernetes

CUDA

cuDNN

NCCL

TensorRT

Nsight

Triton

Terraform

Ansible

GCP

AWS

Azure

OCI

NVIDIA NIMs/DGX

Vector databases

Job description

Quantiphi seeks a Senior Platform Engineer to design, optimize, and scale GenAI infrastructure. You will lead multi-GPU environments, GPU profiling, and distributed training, partnering with data science, MLOps, and application teams for production deployments.

Ideal candidates have hands-on OpenShift/Kubernetes, NVIDIA GPU stack expertise, and IaC skills. This remote US/Canada role offers growth, collaboration with Fortune 500 clients, and cutting-edge AI workloads.