Staff Network Platform Engineer – GPU Cloud Automation

CoreWeave

New York (NY)

Sur place

USD 180 000 - 260 000

Plein temps

14 jours+

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Un CV et une lettre de motivation personnalisés, prêts à envoyer.

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Avantages offerts par ce poste

Medical insurance
Dental insurance
Vision insurance
Life Insurance
Disability insurance
Flexible Spending Account
Health Savings Account
Tuition Reimbursement
Employee Stock Purchase Program (ESPP)
Mental Wellness Benefits
Family-Forming support
Parental Leave
Childcare support
401(k) with employer match
Flexible PTO
Catered lunch

Résumé du poste

CoreWeave is seeking a seasoned software engineer to design and develop automated provisioning, configuration, and monitoring for a large-scale GPU cloud network.

You will lead architectural decisions, influence technical direction, and mentor engineers to improve reliability and reduce toil in a demanding platform environment.

Collaborate across teams, implement robust CI/CD pipelines, and optimize performance for production workloads.

Qualifications

  • Requires 8+ years of professional software engineering experience.
  • Strong proficiency in Python and Go.
  • Solid understanding of networking fundamentals and experience with infrastructure automation tools like Ansible and Kubernetes.

Responsabilités

  • Design and develop software platforms that automate provisioning, configuration, and monitoring of a large-scale GPU cloud network.
  • Lead technical direction through architecture decisions and mentor other engineers to improve system reliability and reduce manual toil.

Connaissances

Python
Go
CI/CD
Network Automation
Kubernetes
Linux
Ansible
Jinja
NetBox
Prometheus
Grafana
IP Addressing
Routing
Switching
DNS
NTP

Outils

Kubernetes
Ansible
Jinja
NetBox
Prometheus
Grafana

Description du poste

CoreWeave is seeking a seasoned software engineer to design and develop automated provisioning, configuration, and monitoring for a large-scale GPU cloud network.

You will lead architectural decisions, influence technical direction, and mentor engineers to improve reliability and reduce toil in a demanding platform environment.

Collaborate across teams, implement robust CI/CD pipelines, and optimize performance for production workloads.

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