GenAI Platform Engineer — Multi-GPU & MLOps

quantiphi; Boston (MA); Hybrid; USD 140,000 - 190,000; Full time

Job summary

Quantiphi is seeking a Senior - Platform Engineer to design, optimize, and scale GenAI infrastructure. You’ll work across multi-GPU environments, profiling GPU performance and supporting production-grade deployments.

Collaboration with data science, MLOps, and application teams is key to delivering cutting-edge AI solutions. Ideal candidates have deep Linux expertise, hands-on with Slurm, OpenShift/Kubernetes, and NVIDIA GPU ecosystems, plus IaC skills with Terraform and Helm.

Qualifications

• Strong 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, Nsight, Triton/TensorRT).
• Strong foundation in Linux systems, performance tuning, and multi-GPU optimization.
• Experience deploying GenAI workloads (LLM fine-tuning, RAG pipelines, multi-modal systems).

Responsibilities

• Design scalable infrastructure for LLM and GenAI workloads across multi-GPU environments.
• Perform GPU profiling, benchmarking, and performance optimization for distributed training workloads.
• Manage compute resources using Slurm clusters and OpenShift/Kubernetes environments.
• Enable and optimize the NVIDIA GPU stack (CUDA, cuDNN, NCCL, Triton, TensorRT).
• Collaborate with data science, MLOps and engineering teams to deploy models.
• Build reusable infrastructure templates with Terraform and Helm.
• Support PoCs and client-facing delivery engagements.

Skills

Slurm

OpenShift

Kubernetes

NVIDIA CUDA

GPU profiling

Distributed training

Tools

Terraform

Ansible

Helm

OpenShift tooling

Job description

Quantiphi is seeking a Senior - Platform Engineer to design, optimize, and scale GenAI infrastructure. You’ll work across multi-GPU environments, profiling GPU performance and supporting production-grade deployments.

Collaboration with data science, MLOps, and application teams is key to delivering cutting-edge AI solutions. Ideal candidates have deep Linux expertise, hands-on with Slurm, OpenShift/Kubernetes, and NVIDIA GPU ecosystems, plus IaC skills with Terraform and Helm.