Senior Staff Engineer - AI HPC Storage & Data Infra

Together Computer Inc; Amsterdam; Hybrid; EUR 120,000 - 180,000; Full time

Job summary

Together AI is seeking a highly experienced storage engineer to design and deliver multi-petabyte storage systems for AI training and inference workloads. You will architect high-performance parallel filesystems and object stores, integrating WekaFS, Ceph, Lustre, and driving cost optimization and scalability across large clusters.

Your role includes building Kubernetes-native storage operators, ensuring multi- tenancy, automated provisioning, and high uptime while collaborating with ML/SRE

Qualifications

• 8+ years in storage engineering at multi-petabyte scale.
• Proven track record deploying and operating high-performance storage for GPU/HPC clusters.
• Deep Kubernetes and cloud-native storage experience in production environments.
• Strong coding skills in Go and Python with demonstrated ability to build production-grade tools.
• BS/MS in Computer Science, Engineering, or equivalent practical experience.
• History of technical leadership: improving performance or uptime or cost efficiency.
• Distributed Storage Systems: expertise in WekaFS, Lustre, GPFS, BeeGFS at multi-petabyte scale.
• Object Storage: experience with S3/MinIO/Ceph or compatible, performance optimization and cost management

Responsibilities

• Design multi-petabyte AI/ML storage systems; integrate WekaFS, Ceph, etc.; lead capacity planning and cost optimization (30-50% savings via tiering, lifecycle policies, right-sizing).
• Design/optimize RDMA, InfiniBand, 400GbE networks; tune for max throughput/min latency; implement NVMe-oF/iSCSI; troubleshoot bottlenecks; optimize TCP/IP for storage.
• Build Kubernetes storage operators/controllers; enable automated provisioning, self-service abstractions, multi-tenant isolation, quotas; create reusable Helm/Terraform patterns.
• Deliver 10-50 GB/s per GPU node; optimize caching (weights/datasets/checkpoints), parallel filesystems, and data paths; troubleshoot with profiling tools; scale to thousands of nodes.
• Build multi-tier caches (local NVMe, distributed, object); optimize data locality and model-weight distribution; implement smart prefetching/eviction.
• Implement monitoring, alerting, SLOs; design DR/backups with runbooks; run chaos engineering; ensure 99.9%+ uptime via proactive/automated remediation.
• Partner with ML/SRE teams; mentor storage best practices; contribute to open-source; write docs, postmortems, and public learnings.

Skills

Storage engineering

Distributed storage

Kubernetes

Go

Python

Linux storage

Networking

Cost optimization

Leadership

Performance tuning

Education

BS/MS in Computer Science or related

Tools

WekaFS

Ceph

Lustre

GPFS

BeeGFS

NVMe-oF

iSCSI

RDMA

Terraform

Helm

Ansible

GitOps

Job description

Together AI is seeking a highly experienced storage engineer to design and deliver multi-petabyte storage systems for AI training and inference workloads. You will architect high-performance parallel filesystems and object stores, integrating WekaFS, Ceph, Lustre, and driving cost optimization and scalability across large clusters.

Your role includes building Kubernetes-native storage operators, ensuring multi- tenancy, automated provisioning, and high uptime while collaborating with ML/SRE