Senior Data Infrastructure Engineer for GPU AI Clusters

Fireworks; San Mateo (CA); On-site; USD 230,000 - 300,000; Full time

Job summary

Fireworks is building a unified, high-performance data layer to support GPU workloads across clouds. The role focuses on storage systems, caching, and KV-style data paths, with emphasis on performance, reliability, and scale.

You will design, implement, and operate distributed storage and data movement components for training and inference. Ideal candidates have deep experience with distributed storage, Kubernetes CSI, and large-scale AI clusters, plus hands-on know-how across the storage stack

Qualifications

• Bachelor's degree in Computer Science, Engineering, or a related technical field (or equivalent practical experience).
• 5+ years of experience designing, building and operating storage, caching or data infrastructure in production at scale.
• Strong software development skills in C/C++, Rust or Go, with experience writing performance-critical data path code. Python or Go for automation.
• Deep understanding of distributed storage fundamentals: consistency models, replication and consensus (e.g., Raft/Paxos), metadata scaling, caching, and failure recovery.
• Hands‑on experience with Kubernetes, including CSI, to mount high-performance volumes into epoxy GPU pods.
• Experience deploying and operating storage clusters (e.g., WEKA, VAST, Lustre, Ceph, MinIO) across clouds using infrastructure-as-code tools such as Terraform or Pulumi.
• Proficiency with performance benchmarking and profiling tools (e.g., fio, iperf3, NCCL tests, perf, eBPF) to identify and resolve bottlenecks across the kernel, network, cache and storage backend.

Responsibilities

• Build and operate high-performance storage, caching, and data infrastructure for GPUs at scale.
• Design and optimize data placement, replication, and movement across clouds.
• Collaborate with AI infra and training teams to minimize data-staging and cold-start delays.
• Contribute to core storage/caching primitives and performance tuning for large-scale AI workloads.

Skills

C/C++

Rust

Go

Python

Education

Bachelor's degree in CS/Engineering

Tools

Kubernetes

CSI

Terraform

Pulumi

WEKA

VAST

Lustre

Ceph

MinIO

Job description

Fireworks is building a unified, high-performance data layer to support GPU workloads across clouds. The role focuses on storage systems, caching, and KV-style data paths, with emphasis on performance, reliability, and scale.

You will design, implement, and operate distributed storage and data movement components for training and inference. Ideal candidates have deep experience with distributed storage, Kubernetes CSI, and large-scale AI clusters, plus hands-on know-how across the storage stack