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CoreWeave

Rents GPU cloud computing for AI developers

Senior Specialist Field Engineer - Storage

Implementation & Technical Account ManagementUpdated on Nov 13
Full-time

About the Job

Requirements

  • A B.S. in Computer Science or a related technical discipline, or equivalent experience.
  • At least 7 years of experience building or operating large-scale storage systems as a storage, systems, or software engineer, or in a deeply technical storage-focused field role.
  • Working knowledge of NFS v3 and v4, including mount options such as nconnect and failure modes, and S3-compatible object storage.
  • Hands-on experience with a distributed or parallel filesystem such as VAST, WEKA, Lustre, or Spectrum Scale.
  • Deep understanding of Kubernetes storage, including CSI drivers, persistent volumes, persistent volume claims, and StorageClasses, and how to troubleshoot them.
  • Ability to benchmark with fio, interpret results, and distinguish metadata-bound workloads from bandwidth-bound workloads.
  • Ability to explain technical problems clearly to engineers and executives and build trust with customers.

Responsibilities

  • Design storage architecture for complex customers, including shared filesystems, object storage, caching, multi-tenant isolation, and cross-region data, and assess failure modes and their effects.
  • Troubleshoot issues from application I/O patterns through the NFS client, CSI driver, storage network, and storage cluster.
  • Identify product gaps for real workloads and work with engineering to address them as an extended member of the Storage team.
  • Lead customer technical overviews, proofs of concept, and workshops, with occasional travel.

Desired Qualifications

  • Debug NFS over TCP at scale, including storage problems caused by network issues such as retransmits, stale routes, and overlay-versus-underlay behavior.
  • Experience with storage for AI workloads, including streaming training data, checkpointing at scale, and read caching.
  • Diagnose failures that emerge only at scale, such as lock exhaustion under heavy concurrency or rename races that corrupt checkpoints.
  • Read storage-system source code to connect production behavior to the code and fix small bugs.
  • Contribute to storage open source projects, including kernel NFS, Lustre, Ceph, or CSI drivers, or publish work on filesystem design or storage performance.

About the Company

CoreWeave

Rents GPU cloud computing for AI developers

CoreWeave rents cloud computing to AI labs and businesses that train models and run them in production for research and commercial applications. Its platform combines NVIDIA graphics chips, storage, networking, and software built for demanding AI workloads across connected clusters scaled to fit each project. CoreWeave Forge connects tools for tracking experiments, testing models, and improving AI systems using feedback from production. Customers rent computing capacity through committed contracts or usage charges, while managed services handle the infrastructure needed to keep large workloads running. CoreWeave was founded in 2017 and is headquartered in Livingston, New Jersey.

Company size
1,001-5,000
Company stage
IPO
Headquarters
Livingston, NJ
Founded
2017

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