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Member of Technical Staff

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Member of Technical Staff in USA

  • Fireworks AI
  • Full time
  • Email
  • San Mateo, CA

Responsibilities

  • Design and build a unified, high-performance data layer for GPU training and inference workloads.
  • Store, cache, replicate, and move datasets, checkpoints, model weights, and KV cache across clouds and storage tiers.
  • Develop performance-critical data-path software in C/C++, Rust, or Go, with Python or Go automation where appropriate.
  • Address distributed storage concerns including consistency models, replication, consensus, metadata scaling, caching, compaction, and failure recovery.
  • Deploy and operate storage clusters and mount high-performance volumes into ephemeral GPU pods using Kubernetes and CSI.
  • Benchmark and profile kernel, network, cache, and storage performance to identify and resolve bottlenecks.
  • Support high-performance networking and data movement using RDMA, RoCE v2, InfiniBand, and GPUDirect Storage.

Requirements

  • Bachelor’s degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.
  • At least 5 years of experience designing, building, and operating production-scale storage, caching, or data infrastructure.
  • Strong software development skills in C/C++, Rust, or Go, including performance-critical data-path code.
  • Deep understanding of distributed storage fundamentals, including consistency models, replication, consensus, metadata scaling, caching, and failure recovery.
  • Hands-on Kubernetes experience, including CSI, for high-performance volumes and ephemeral GPU pods.
  • Experience deploying and operating storage clusters such as WEKA, VAST, Lustre, Ceph, or MinIO across clouds with Terraform or Pulumi.
  • Proficiency with performance benchmarking and profiling tools such as fio, iperf3, NCCL tests, perf, and eBPF.
  • Preferred experience contributing to or owning storage, caching, or key-value systems such as Ceph, Alluxio, JuiceFS, RocksDB, FoundationDB, TiKV, Redis, Dragonfly, SeaweedFS, or MinIO.
  • Preferred experience with HPC or large-scale AI clusters, Slurm, Kubernetes GPU pools, AI I/O patterns, Linux internals, high-performance networking, GPUDirect Storage, and petabyte-scale cross-cloud data movement.
  • Preference for experience with software-defined storage rather than proprietary hardware appliances.

Benefits

  • Work on challenging AI infrastructure problems involving low-latency inference and scalable model serving.
  • Collaborate with engineers and AI researchers in a fast-growing, inclusive environment.
  • The posting describes ownership, direct impact, limited bureaucracy, and access to cutting-edge technology.

Salary: $175k - $220k/yr

Fireworks AI

Fireworks is the fastest way to build, tune, and scale AI on open models. Ship production-ready AI in seconds on our globally distributed cloud infrastructure, optimized for your use case. Fireworks powers production workloads at companies like Uber, Doordash, Notion, and Cursor—delivering 15× fa...

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