Senior MLOps Engineer: Scale AI Pipelines & Open-Source

NVIDIA; United Kingdom; On-site; GBP 58,000 - 129,000; Full time

Benefits offered by this job

Competitive salary

Generous benefits

Job summary

NVIDIA is seeking a Senior MLOps Engineer to join our DSX Enablement team, collaborating with customers to implement and optimize AI workloads. You will design ML infrastructure, guide production ML systems, and improve end-to-end pipelines across training and inference.

You will work with Linux, Kubernetes, and modern ML frameworks, profiling large-scale workloads and contributing open-source tools and reference architectures to simplify building and managing AI systems at scale.

Qualifications

• 8+ years in data science, data engineering, or ML engineering in large-scale systems.

Responsibilities

• Develop innovative AI infrastructure solutions and ML workloads.
• Advise on ML workload demands and diagnose full-stack AI/ML system problems.
• Lead optimization of training/inference pipelines on DGX Cloud and NCPs.
• Profile and tune large-scale training/inference workloads for latency and cost.
• Create open-source tools and reference architectures for ML workloads at scale.

Skills

Linux

Kubernetes

Python

C++

Go

Rust

Education

BS/MS/PhD in CS or related field

Tools

CUDA

NeMo

RAPIDS

Triton

DGX

NVLink/InfiniBand

Job description

NVIDIA is seeking a Senior MLOps Engineer to join our DSX Enablement team, collaborating with customers to implement and optimize AI workloads. You will design ML infrastructure, guide production ML systems, and improve end-to-end pipelines across training and inference.

You will work with Linux, Kubernetes, and modern ML frameworks, profiling large-scale workloads and contributing open-source tools and reference architectures to simplify building and managing AI systems at scale.