Senior MLOps Engineer: AI Infrastructure & Scale

NVIDIA

Poland

On-site

PLN 293,000 - 650,000

Full time

14 days+

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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 strategic customers to implement and enhance AI workloads. You will build and deploy AI solutions on NeoCloud and NVIDIA Cloud Partners, optimize training and inference, and develop open-source tools for scalable ML systems.

You will guide internal and external customers, work with infrastructure software teams, and help reduce latency, cost, and risk while advancing AI capabilities across industries.

Qualifications

  • BS, MS, or Ph.D. in Computer Science, Engineering, or related field, or equivalent experience.
  • 8+ years in data science, data engineering, or ML engineering in large-scale production environments.
  • Experience across the ML lifecycle from exploration to production.
  • Systems topics including Linux, schedulers, Kubernetes, distributed filesystems, and datacenter networking.
  • Scripting and programming in Bash and Python; systems programming in C++, Go, or Rust.

Responsibilities

  • Develop innovative AI infrastructure capabilities and ML workloads.
  • Advise on demands of ML workloads for production systems.
  • Diagnose and solve full-stack AI/ML system problems for customers.

Skills

Linux
Kubernetes
Python
Bash
C++
Go
Rust
ML frameworks
Data engineering
Communication

Education

BS/MS/PhD in CS/EE

Tools

CUDA
NeMo
RAPIDS
Triton
DGX
InfiniBand

Job description

NVIDIA is seeking a Senior MLOps Engineer to join our DSX Enablement team, collaborating with strategic customers to implement and enhance AI workloads. You will build and deploy AI solutions on NeoCloud and NVIDIA Cloud Partners, optimize training and inference, and develop open-source tools for scalable ML systems.

You will guide internal and external customers, work with infrastructure software teams, and help reduce latency, cost, and risk while advancing AI capabilities across industries.

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