Senior Distributed Storage Software Engineer - Linux/Perl/Python

NVIDIA Corporation

United States

Vor Ort

USD 184.000 - 288.000

Vollzeit

Vor 3 Tagen
Sei unter den ersten Bewerbenden

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Zusammenfassung

NVIDIA Corporation is seeking a senior software development engineer to design and deploy software storage management systems for its worldwide design engineering teams in the US. You will collaborate across hardware and software groups to create scalable storage solutions, using Perl and Python, while prioritizing performance, reliability, and efficiency.

Role emphasizes architectural decisions backed by data, cross-team collaboration, and driving improvements in design and testing processes to

Qualifikationen

  • Development background in Linux software development and distributed storage systems.
  • Understanding of storage concepts like volumes, snapshots, clones, and deduplication.
  • Ability to drive architectural decisions from data and estimates to balance cost, performance, reliability, and scalability.

Aufgaben

  • Collaborate with HW and SW teams to define new features for distributed storage systems.
  • Develop scalable storage management solutions in Perl and Python.
  • Optimize workflow efficiency and scalability with internal customers.
  • Improve software design and testing processes to boost velocity and quality.
  • Contribute to time-to-market for next-gen hardware products and technologies.

Kenntnisse

Linux development
Storage systems
Distributed systems
Perl
Python
Data-driven design
Team collaboration

Ausbildung

BS in Computer Science

Tools

DevOps tools
Cursor AI
NetApp systems

Jobbeschreibung

NVIDIA Corporation is seeking a senior software development engineer to design and deploy software storage management systems for its worldwide design engineering teams in the US. You will collaborate across hardware and software groups to create scalable storage solutions, using Perl and Python, while prioritizing performance, reliability, and efficiency.

Role emphasizes architectural decisions backed by data, cross-team collaboration, and driving improvements in design and testing processes to

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