C
CoreWeave
Staff Software Engineer (Cluster Orchestration)
Skills
Machine LearningAIKubernetes
2 months ago
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Important information
Contract type:
Permanent
Salary:
$185,000 – $275,000 / year
Location:
Sunnyvale, CA, USA
Work mode:
Onsite
Published on:
29 August 2026
What they need
- As part of the Cluster Orchestration team, you will play a key role in advancing CoreWeave’s orchestration platform including SUNK (Slurm on Kubernetes) and beyond, our Kubernetes-native foundation that powers AI training and inference at scale
- This is an opportunity to help shape one of the most critical layers of the AI cloud: ensuring workloads run seamlessly, reliably, and efficiently across massive GPU clusters
- By building the systems that eliminate infrastructure bottlenecks and create new orchestration capabilities, you will directly empower customers to innovate faster and push the boundaries of what’s possible with AI
- As a Staff Engineer, you will be a technical leader shaping the long-term strategy for CoreWeave’s orchestration platform
- You’ll define architectural direction, own critical parts of the orchestration platform and other managed services, and drive cross-org initiatives in scheduling, quota enforcement, and scaling at hyperscale
- You’ll mentor senior engineers, establish org-wide best practices in reliability and observability, and ensure CoreWeave’s orchestration layer evolves to meet the demands of next-generation AI workloads- 8+ years of software engineering experience
- Proven track record designing and operating large-scale distributed systems in production
- Experience setting technical direction and influencing cross-team architecture
- Advanced proficiency in Go and distributed systems design and cloud-native development
- Deep expertise in Slurm/Kubernetes internals and cloud-native development
- Bachelor’s or Master’s degree in CS, EE, or related field
- Deep expertise in Slurm/Kubernetes internals
- Familiarity with orchestration and workflow technologies such as Ray, Kubeflow, Kueue, Istio, Knative, or Argo Workflows
- Experience with distributed workloads, GPU-based applications, or ML pipelines
- Knowledge of scheduling concepts like quota enforcement, pre-emption, and scaling strategies
- Exposure to reliability practices including SLOs, alarms, and post-incident reviews
- Experience with AI infrastructure and workloads (ML training, inference, or HPC)
- Ability to mentor senior engineers and elevate organizational standards
- You thrive on solving problems that balance cost, performance, and reliability in high-demand environments
- You’re curious about orchestration beyond SUNK and how to evolve it for next-generation AI
- You love defining long-term architecture for systems at global scale
- You’re an expert at mentorship, architecture, and operational excellence across teams
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