Senior MLOps Engineer: AI Infra Architect

NVIDIA; United States; Remote; USD 184,000 - 357,000; Full time

Benefits offered by this job

Equity

Benefits

Job summary

NVIDIA is seeking a Senior MLOps Engineer to join the DSX Enablement team to collaborate with strategic customers on AI workloads. You will build and optimize ML pipelines, train and deploy at scale on NeoCloud and NCP platforms, and act as the technical lead for joint engagements across DGX Cloud.

The role requires 8+ years in ML engineering or related fields and strong Linux/Kubernetes experience, plus proficiency in Python and C++/Go/Rust. Equity and comprehensive benefits are offered.

Qualifications

• BS, MS, or Ph.D. in CS, CS/EE, or related field, or equivalent experience.
• 8+ years in data science, data engineering, or ML engineering for large-scale systems.
• Experience across ML lifecycle from exploration to production.
• Proficiency with Linux, Kubernetes, distributed filesystems, and datacenter networking.
• Strong scripting and programming: Bash, Python; systems programming in C++, Go, or Rust.
• Experience with ML/DL frameworks for training and inference.

Responsibilities

• Develop innovative AI infrastructure solutions.
• Advise infrastructure teams on ML workloads.
• Diagnose and solve full-stack AI/ML system problems.
• Lead AI/ML initiatives on DGX Cloud and NCPs.
• Build and deploy AI solutions on NeoCloud platforms.
• Be primary technical contact for customers and partners.
• Profile and tune large-scale training and inference workloads.
• Develop open-source tools and reference architectures.

Skills

Linux

Kubernetes

Python

C++

Go

Rust

ML frameworks

Distributed training

Education

BS/MS/PhD in CS/EE or related

Tools

CUDA

NeMo

RAPIDS

Triton

DGX

Job description

NVIDIA is seeking a Senior MLOps Engineer to join the DSX Enablement team to collaborate with strategic customers on AI workloads. You will build and optimize ML pipelines, train and deploy at scale on NeoCloud and NCP platforms, and act as the technical lead for joint engagements across DGX Cloud.

The role requires 8+ years in ML engineering or related fields and strong Linux/Kubernetes experience, plus proficiency in Python and C++/Go/Rust. Equity and comprehensive benefits are offered.