Senior MLOps Engineer: Scale AI Pipelines & DGX Cloud

NVIDIA AI; Indiana (PA); On-site; USD 160,000 - 210,000; Full time

Job summary

NVIDIA is seeking a Senior MLOps Engineer to join the DSX Enablement team, collaborating with customers to implement and enhance AI workloads. You will build AI solutions on NeoCloud and DGX/NG Cloud platforms, tune distributed training, and help optimize production ML pipelines across frameworks.

You will engage as a primary technical contact for customers, guide joint engagements, and contribute to open-source tools and reference architectures for scalable AI systems, including exploration of

Qualifications

• BS/MS/PhD in CS, EE, or related field, or equivalent experience.
• 8+ years in data science, data engineering, or ML engineering for large-scale systems.
• AI/ML lifecycle experience from exploration to production.
• Linux, batch schedulers, Kubernetes, distributed filesystems, datacenter networking.
• Scripting in Bash and Python; systems programming in C++, Go, or Rust.
• Experience with ML frameworks for training and inference.
• Excellent communication and ability to present architectures to engineers and leadership.
• Strong engineering discipline and track record on meaningful projects.

Responsibilities

• Develop solutions advancing AI infrastructure capabilities and ML workloads.
• Advise on demands of ML workloads and diagnose full-stack AI/ML issues.
• Collaborate with teams building infrastructure software and accelerated frameworks.
• Profile and tune large-scale training/inference workloads on NVIDIA platforms.
• Contribute open-source tools and reference architectures for scalable ML workloads.

Skills

Communication & presentation

Scripting & programming

Linux OS

Python

C++

Go

Rust

bash

Kubernetes

ML frameworks

Education

BS/MS/PhD in CS/EE or related

Tools

DGX Cloud

Linux

Distributed filesystems

Networking (datacenter)

Job description

NVIDIA is seeking a Senior MLOps Engineer to join the DSX Enablement team, collaborating with customers to implement and enhance AI workloads. You will build AI solutions on NeoCloud and DGX/NG Cloud platforms, tune distributed training, and help optimize production ML pipelines across frameworks.

You will engage as a primary technical contact for customers, guide joint engagements, and contribute to open-source tools and reference architectures for scalable AI systems, including exploration of