Senior Kubernetes & Slurm Architect for AI Scale

Coreweave

Singapore

In loco

SGD 180.000 - 320.000

Tempo pieno

14 giorni+

Una candidatura completa in un minuto

Curriculum e lettera di presentazione personalizzati, pronti da inviare.

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Vantaggi offerti da questo lavoro

Equity
Flexible vacation policy
Comprehensive benefits

Descrizione del lavoro

CoreWeave is seeking a Software Engineer, Cluster Orch (SUNK) to shape the long-term architecture of the orchestration platform. You will own key components, drive cross-team initiatives in scheduling and quota enforcement, and mentor senior engineers to elevate reliability and performance across massive GPU clusters.

You will lead efforts around platform reliability, observability, and scaling, while defining technical direction and best practices for multi-tenant cloud workloads at scale.

Competenze

  • 8+ years of professional software engineering in production.
  • Go and distributed systems design proficiency required.
  • Kubernetes internals or cloud-native development desirable.
  • Experience mentoring engineers and guiding architecture across teams.

Mansioni

  • Define long-term architecture for CoreWeave's orchestration platform.
  • Own critical components of the orchestration layers and managed services.
  • Drive cross-organisational initiatives in scheduling and resource scaling.
  • Mentor senior engineers and elevate engineering standards.

Conoscenze

8+ yrs exp
Go
Distributed systems
Kubernetes
Slurm
Mentoring

Formazione

Bachelor's in CS or related

Strumenti

Ray
Kubeflow
Istio
Knative
Argo Workflows

Descrizione del lavoro

CoreWeave is seeking a Software Engineer, Cluster Orch (SUNK) to shape the long-term architecture of the orchestration platform. You will own key components, drive cross-team initiatives in scheduling and quota enforcement, and mentor senior engineers to elevate reliability and performance across massive GPU clusters.

You will lead efforts around platform reliability, observability, and scaling, while defining technical direction and best practices for multi-tenant cloud workloads at scale.

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