Storage Engineer, zDATA

ZETTABYTES, INC.
Palo Alto, CA, United States
4 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
5 years minimum
Compensation
$180,000 - $230,000
Working hours
Regular working hours

Tech stack

Artificial Intelligence Amazon S3 Software Applications Bash Shell Cloud Computing Computer Clusters Computer Programming Customer Data Management Data Centers Extract Transform Load (ETL) Linux Disaster Recovery
+17 more
File Systems General Parallel File Systems Information Lifecycle Management Python (Programming Language) Networking Basics Open Source Technology Performance Tuning Remote Direct Memory Access Weka Ceph (Software) Scripting Graphics Processing Unit (GPU) Computer Network Operations Kubernetes Storage Technologies Deployment Automation Model Inference

Job description

Storage Engineer, zDATASkip to main content, * AI computing company: we turn GPU hardware into reliable, high-utilisation AI compute through software, orchestration and full lifecycle operations

  • What we offer: enterprise GPU cloud and AI inference, software for data centre owners to run their own GPU clouds, turnkey and sovereign AI data centres, edge computing and GPU financing
  • Who we work with: GPU owners, data centre operators, enterprises, OEMs, integrators and financiers across multiple markets
  • How we work: fast-moving and high-accountability; we value speed, ambition, clarity, ownership and measurable outcomes

Role Summary

The Storage Engineer, zDATA builds and operates the storage services that feed data to AI training and inference workloads on Zettabytes platform.

The role covers high-performance file and object storage, from architecture and performance tuning to data protection and day-to-day operations.

The Storage Engineer works with platform, networking and product teams so that storage keeps pace with the GPUs it serves.

Reporting Line

Reports to: Co-CTO and CPO

Key Responsibilities

  • Architecture: design storage tiers for AI workloads, balancing throughput, capacity, durability and cost.
  • Deployment: deploy and integrate parallel file systems and object storage with GPU clusters and Kubernetes.
  • Performance: benchmark and tune storage for data loading, checkpointing and model distribution.
  • Data protection: implement snapshots, replication, backup and recovery procedures that meet customer requirements.
  • Multi-tenancy: provide quotas, access controls and isolation for customer data on shared infrastructure.
  • Operations: monitor capacity and health, respond to storage incidents and drive root-cause fixes.
  • Product input: work with the Product Manager, zDATA on the roadmap, customer requirements and service levels.
  • Automation: automate provisioning, upgrades and routine tasks with infrastructure as code.

Requirements

Storage Software, Cloud Computing, Artificial Intelligence (AI), GPU (Graphics Processing Unit), High Tech Industry, Computer Software, Network Operations Center, OEM (Original Equipment Manufacturer), Storage Software, Performance Tuning/Optimization, * 5+ years in storage engineering or infrastructure for large-scale systems

  • Hands-on experience with parallel file systems (Lustre, GPFS, WEKA, VAST or equivalent) or Ceph
  • Solid knowledge of S3-compatible object storage
  • Strong Linux and networking fundamentals, including NFS and RDMA
  • Programming or scripting in Go, Python or Bash
  • Experience with Kubernetes storage (CSI drivers, persistent volumes)

Bonus Qualifications

  • Experience with GPUDirect Storage or similar data paths
  • Background in storage for AI training or HPC
  • Experience with data lifecycle and tiering policies
  • Contributions to open-source storage projects

Benefits & conditions

What Success Looks Like (First 90 to 180 Days)

  • Storage performance baselines are published for priority workloads
  • Backup and recovery procedures are tested and documented
  • Provisioning of customer storage is automated
  • Capacity forecasts are shared with product and finance teams every month

Why This Role Matters

  • GPU efficiency: slow storage leaves expensive GPUs idle, and this role prevents that.
  • Customer data: customers trust zDATA with valuable datasets and models, and this role keeps them safe.

Working Norms at Zettabyte

  • Bias to action: deliver drafts quickly, then iterate on feedback
  • Be precise: double-check numbers and facts; sloppy analysis creates downstream cost
  • Make it usable: package outputs for decision-making, not data dumps
  • Own the process: whoever drives a deliverable manages stakeholders and timelines
  • Learn the ecosystem: understand GPUs, cluster operations and the buyer landscape, * Compensation: USD 180,000 to 230,000 a year base salary, plus equity
  • Benefits: Medical, dental and vision insurance; 401(k) retirement plan; paid time off and US public holidays; equity
  • Work authorisation: Required in the United States
  • Equal opportunity: Zettabyte is an equal opportunity employer; qualified applicants with arrest or conviction records will be considered in line with the California Fair Chance Act

About the company

Zettabyte is a supplier of the United Nations Global Marketplace (UNGM #1117361) and is committed to aiding the United Nations in achieving its Sustainable Development Goals.

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