Data Infrastructure Storage Engineer
Job Summary
To solve data challenges for GPU workloads, the full-time hybrid Data Infrastructure Storage Engineer will design and implement a high-performance data layer that manages data storage, caching, and movement across multiple clouds, ensuring seamless access for training and inference teams.
Key responsibilities
- Build and maintain a unified data layer that spans various storage systems, ensuring optimal data placement and retrieval
- Design and implement caching strategies to enhance performance and reduce latency for AI workloads
- Collaborate with cross-functional teams to ensure data infrastructure meets the needs of production AI applications
Required qualifications
- Bachelor's degree in Computer Science, Engineering, or a related technical field (or equivalent practical experience)
- 5+ years of experience in designing, building, and operating storage or data infrastructure in production environments
- Strong software development skills in C/C++, Rust, or Go, with experience in performance-critical data path coding
- Deep understanding of distributed storage fundamentals, including consistency models and replication
- Hands-on experience with Kubernetes and deploying storage clusters across clouds using infrastructure-as-code tools
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