AI/ML Infra Engineer — GPU Clusters & HPC

NVIDIA AI; Redmond (WA); On-site; USD 120,000 - 180,000; Full time

Benefits offered by this job

Competitive salaries

Comprehensive benefits package

Equity

Job summary

NVIDIA AI in Redmond seeks a recent graduate with an MS/PhD in CS to collaborate with AI/ML research teams, identify infrastructure gaps, and implement scalable solutions on GPU clusters.

You will monitor performance, optimize for high availability, and ensure researchers have efficient resources using PyTorch, Kubernetes, Slurm, and Docker.

Role focuses on distributed training, data processing, and model inference across HPC workloads with equity and comprehensive benefits.

Qualifications

• MS/PhD in CS or equivalent with HPC/accelerated computing exposure.
• Experience with distributed training and GPU-accelerated frameworks.
• Proficiency in Python; familiarity with Go is a plus.

Responsibilities

• Collaborate with AI/ML research teams to identify gaps and implement scalable GPU infra.
• Monitor and optimize infrastructure performance for high availability.
• Ensure efficient resource utilization for researchers and their workloads.

Skills

AI/ML Infrastructure

HPC Workloads

GPU Computing

PyTorch

Kubernetes

Slurm

Docker

Python

Go

Bash

Distributed Training

Infiniband

Cloud Computing

Data Processing

Model Inference

Parallel Computing

Education

MS in Computer Science

PhD in Computer Science

Equivalent experience

Tools

Kubernetes

Slurm

Docker

Job description

NVIDIA AI in Redmond seeks a recent graduate with an MS/PhD in CS to collaborate with AI/ML research teams, identify infrastructure gaps, and implement scalable solutions on GPU clusters.

You will monitor performance, optimize for high availability, and ensure researchers have efficient resources using PyTorch, Kubernetes, Slurm, and Docker.

Role focuses on distributed training, data processing, and model inference across HPC workloads with equity and comprehensive benefits.