Senior AI Infra & MLOps Engineer

NVIDIA AI; Layer-de-la-Haye; On-site; GBP 90,000 - 140,000; 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 develop solutions on NeoCloud, advise on ML workloads, and help diagnose full-stack AI system problems.

You will work with teams building infrastructure software and accelerated frameworks to support today’s compelling AI applications. You will profile and tune large-scale training and inference workloads on NVIDIA Cloud Partners, aiming to

Qualifications

• BS, MS, or PhD in Computer Science, Engineering or related field, or equivalent experience.
• 8+ years in data science/ML/engineering roles with large-scale systems.
• AI/ML lifecycle experience from exploration to production.
• Linux, schedulers, Kubernetes, distributed filesystems, and datacenter networking.
• Fluent scripting with Bash and Python; systems programming in C++, Go or Rust.
• Experience with ML frameworks for training and inference.
• Strong communication and ability to present architectures and trade-offs.

Responsibilities

• Develop and deploy AI solutions on NeoCloud and NVIDIA Cloud Partners, incl. distributed training and ML pipelines.
• Serve as technical contact for customers and partners; guide engagements and optimize DGX Cloud deployments.
• Collaborate with infrastructure software teams to support AI applications and frameworks.
• Profile and tune large-scale training/inference workloads to reduce latency and cost.
• Create open-source tools and reference architectures for scalable ML workloads.

Skills

Linux

Kubernetes

Python

C/C++/Rust

Shell scripting (bash)

Batch schedulers

Distributed filesystems

Networking

Go

Rust

Education

BS/MS/PhD in CS/CE or related field

Tools

CUDA

NeMo

RAPIDS

Triton

NIM

InfiniBand

NVLink

RoCE

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 develop solutions on NeoCloud, advise on ML workloads, and help diagnose full-stack AI system problems.

You will work with teams building infrastructure software and accelerated frameworks to support today’s compelling AI applications. You will profile and tune large-scale training and inference workloads on NVIDIA Cloud Partners, aiming to