Senior Go Distributed Systems Engineer — AI Storage Cloud

Nvidia Corporation in

Santa Clara (CA)

On-site

USD 184,000 - 357,000

Full time

14 days+
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Job summary

NVIDIA is seeking a Senior Distributed Software Engineer to help develop distributed storage services for AI/ML in the DGX Cloud ecosystem. You will design, implement, and operate scalable Go programs and cloud-native components deployed on Kubernetes, collaborating with multiple teams to deliver robust, high-performance storage services.

The role emphasizes ownership of architecture and end-to-end delivery, with strong focus on scalability, deployment automation, and reliability across

Qualifications

  • Bachelor's degree in Computer Science or related field, or equivalent experience.
  • 8+ years of industry experience in software engineering.
  • Strong background in distributed systems including Golang, Kubernetes, and cloud provider integrations.
  • Experience delivering distributed services across varied environments.
  • Experience developing and maintaining enterprise software in Kubernetes environments.
  • Excellent communication and presentation skills.

Responsibilities

  • Architect and design distributed storage service optimized for AI/ML.
  • Develop and maintain Go programs and CLI tools in Kubernetes environments.
  • Build features to improve availability and reliability for large-scale deployments.
  • Collaborate with NVIDIA teams and external customers to deliver cloud services.
  • Automate deployment, management, and monitoring of the storage service.

Skills

Golang
Kubernetes
Distributed systems

Education

Bachelor's degree in Computer Science

Job description

NVIDIA is seeking a Senior Distributed Software Engineer to help develop distributed storage services for AI/ML in the DGX Cloud ecosystem. You will design, implement, and operate scalable Go programs and cloud-native components deployed on Kubernetes, collaborating with multiple teams to deliver robust, high-performance storage services.

The role emphasizes ownership of architecture and end-to-end delivery, with strong focus on scalability, deployment automation, and reliability across

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