Senior GPU and HPC Infrastructure Engineer – DGX Cloud

Jobtailor; Deutschland; Vor Ort; EUR 120.000 - 180.000; Vollzeit

Zusammenfassung

Jobtailor is seeking a senior software engineer to help build and automate a platform for GPU asset provisioning, configuration, and lifecycle management across cloud providers. You will own end-to-end automation of datacenter operations for large‑scale machine learning systems, including monitoring, health management, and NVLINK topology.

You will collaborate with hardware, software, and AI training teams to ensure integration from firmware to training applications, and you will help improve

Qualifikationen

• 10+ years of software engineering experience on large-scale production systems.
• BS in Computer Science, Engineering, Physics, Mathematics, or comparable degree or equivalent experience.
• Expert-level knowledge of Go and Python.
• Expert-level Linux system administration and management.
• Experience with cluster management systems (Kubernetes, SLURM).
• Understanding of performance, security, and reliability in distributed systems.

Aufgaben

• Contribute to a platform that automates GPU asset provisioning and lifecycle management across cloud providers.
• Build end-to-end automation of datacenter operations, break/fix, and lifecycle management for large-scale Machine Learning systems.
• Implement monitoring and health management capabilities for reliability, availability, and scalability of GPU assets.
• Manage NVLINK topography across GPU clusters.
• Build automated test infrastructure to qualify distributed systems for operation.
• Collaborate with engineering teams to ensure software integration from hardware to AI training applications.

Kenntnisse

Go

Python

Linux administration

Ausbildung

BS in Computer Science

BS in Engineering

BS in Physics

BS in Mathematics

Tools

Kubernetes

SLURM

Jobbeschreibung

Responsibilities

• Contribute to a platform that automates GPU asset provisioning, configuration, and lifecycle management across cloud providers
• Build end-to-end automation of datacenter operations, break/fix, and lifecycle management for large‑scale Machine Learning systems
• Implement monitoring and health management capabilities that enable reliability, availability, and scalability of GPU assets
• Manage NVLINK topography across GPU clusters
• Build automated test infrastructure to qualify distributed systems for operation
• Collaborate with engineering teams to ensure software integration from hardware to AI training applications

Requirements

• 10+ years of software engineering experience on large‑scale production systems
• BS in Computer Science, Engineering, Physics, Mathematics, or comparable degree or equivalent experience
• Expert-level knowledge of a systems programming language (Go, Python)
• Expert-level knowledge of Linux system administration and management
• Understanding of cluster management systems (Kubernetes, SLURM)
• Understanding of performance, security, and reliability in complex distributed systems
• Familiarity with system‑level architecture, data synchronization, fault tolerance, and state management

Core Competencies

Demonstrates expert-level knowledge in systems programming languages such as Go and Python, along with extensive experience in Linux system administration and management. Proficient in building automated solutions for large-scale Machine Learning systems and managing GPU asset provisioning and lifecycle management across cloud environments.

Certifications & Qualifications

• BS in Computer Science
• BS in Engineering
• BS in Physics
• BS in Mathematics