Senior MLOps Engineer: AI Infrastructure & Scale Expert

NVIDIA; Seattle (WA); On-site; USD 184,000 - 357,000; Full time

Job summary

NVIDIA is seeking a Senior MLOps Engineer to join the DSX Enablement team in Seattle, WA. You will collaborate with strategic customers to implement and optimize AI workloads, building scalable ML pipelines on NeoCloud platforms and with NVIDIA Cloud Partners.

You will guide internal and external customers, tune large-scale training/inference, and help advance AI infrastructure capabilities, including LLM evaluation and open-source tooling across production environments.

Qualifications

• 8+ years in data science, data engineering, or ML engineering for large-scale production systems.
• Experience across AI/ML lifecycle from exploration to production.
• Strong Linux, networking, and datacenter-scale system knowledge.
• Solid scripting in Bash/Python and systems programming in C++, Go, or Rust.
• Experience with ML/DL frameworks for training and inference.
• Excellent communication and ability to present architectures and trade-offs.

Responsibilities

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

Skills

Communication

ML lifecycle

Cross-functional

Problem solving

Perf analysis

Billing/optimization

Python

C++/Go/Rust

Education

BS/MS/PhD in CS/EE or related

Tools

Linux

Kubernetes

Distributed filesystems

Networking at datacenter scale

Python

C++/Go/Rust

CI/CD

Docker

Job description

NVIDIA is seeking a Senior MLOps Engineer to join the DSX Enablement team in Seattle, WA. You will collaborate with strategic customers to implement and optimize AI workloads, building scalable ML pipelines on NeoCloud platforms and with NVIDIA Cloud Partners.

You will guide internal and external customers, tune large-scale training/inference, and help advance AI infrastructure capabilities, including LLM evaluation and open-source tooling across production environments.