The Storage Engine Organisation at CoreWeave is responsible for the product capabilities and data plane function of CoreWeave's managed storage products.
\nWe build reliable, scalable storage solutions with segment leading performance. Storage engine works with engineering teams across infrastructure, compute, and platform to ensure our storage services meet the needs of the world's most demanding AI workloads.
\nThe role involves designing and implementing distributed storage solutions to support scaling data-intensive AI workloads, contributing to the development of exabyte-scale, S3-compatible object storage, and integrating dedicated storage clusters into diverse customer environments.
\nKey responsibilities include working with technologies such as RDMA, GPU Direct Storage, and distributed filesystems protocols like NFS or FUSE to optimise storage performance and efficiency, participating in efforts to improve the reliability, durability, and observability of our storage stack, collaborating with operations teams to monitor, troubleshoot, and improve storage systems in production environments, and helping develop metrics and dashboards to provide visibility into storage performance and health.
\nThe ideal candidate will have a strong background in storage systems engineering or infrastructure, with experience working with object storage or distributed filesystems in production environments, proficiency in a systems programming language like Go, C, or Rust, and familiarity with storage observability tools and telemetry pipelines.
\nAs a senior software engineer, you will be responsible for designing, developing, and deploying scalable and efficient storage solutions, working closely with cross-functional teams to ensure seamless integration with other components of the platform, and mentoring junior engineers to help them grow in their roles.
\nIf you are passionate about building high-performance storage solutions and have a strong background in software engineering, we encourage you to apply for this exciting opportunity.
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\nThe primary responsibilities of this role include designing and implementing distributed storage solutions to support scaling data-intensive AI workloads, contributing to the development of exabyte-scale, S3-compatible object storage, and integrating dedicated storage clusters into diverse customer environments. Additionally, the successful candidate will work with technologies such as RDMA, GPU Direct Storage, and distributed filesystems protocols such as NFS or FUSE to optimize storage performance and efficiency.
\nKey responsibilities also include leading efforts to improve the reliability, durability, security, and observability of our storage stack, collaborating with operations teams to monitor, troubleshoot, and improve storage systems in production environments, setting the bar for developing metrics and dashboards to provide visibility into storage performance and health, analyzing telemetry and system data to drive improvements in throughput, latency, and resilience, and working cross-functionally with platform, product, and infrastructure teams to deliver seamless storage capabilities across the stack.
\nA key aspect of this role is sharing knowledge and mentoring other engineers on best practices in building distributed, high-performance systems.
\nTo be successful in this role, the ideal candidate will have a strong background in storage systems engineering or infrastructure, with a minimum of 8-10 years of experience. They will also have hands-on experience with object storage or distributed filesystems in production environments, as well as proficiency in a systems programming language such as Go, C, or Rust. Additionally, they will have experience working with cloud-native infrastructure, Kubernetes, and scalable system architectures, and familiarity with storage observability tools and telemetry pipelines.
\nIf you're a motivated and experienced engineer looking to join a dynamic team and contribute to the development of cutting-edge storage solutions, we encourage you to apply for this exciting opportunity.
\nXML job scraping automation by YubHub
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