Job Purpose
Provide high?throughput, consistent storage tiers (Scratch/HPS + Object) for large?scale training data ingest, checkpoints, and inference artifacts.
Roles & Responsibilities
Design/expand Lustre/BeeGFS HPS; NVMe?oF and Object (S3) tiers; align with AI dataflow and GDS.
Establish namespace, OST/MDT layout, stripe/RAID policies; tiering for warm/cold datasets.
Capacity/performance planning; rebalance and failover testing; automate snapshots and checkpoint retention.
Proactive detection of hot spots and metadata contention; schema for small?file handling.
Tune RDMA paths, page cache, IO schedulers; validate end?to?end I/O profiles for LLM training/inference.
Lead P0/P1 critical incident response for enterprise-scale AI/ML storage infrastructure supporting NVIDIA GPU clusters, ensuring rapid service restoration and minimal impact to business-critical workloads.
Act as the storage SME during major incidents involving BeeGFS, Lustre, GPFS (IBM Spectrum Scale), NFS, NVMe-oF, Parallel File Systems, and Object Storage platforms.
Perform deep-dive troubleshooting and resolution of storage performance degradation, metadata bottlenecks, I/O latency spikes, filesystem corruption, capacity exhaustion, and hardware failures.
Conduct comprehensive Root Cause Analysis (RCA) for storage-related outages affecting GPU training, inferencing, AI pipelines, and high-performance computing (HPC) workloads.
Backup/DR for critical datasets; test restore time and RPO/RTO regularly; corruption and split?brain handling.
Multi?tenant encryption at rest and in transit, POSIX/ACLs, S3 policies, retention/legal holds.
Experience & Educational Requirement
BE/B-Tech or equivalent with Computer Science or Electronics & Communication
Certification- SNIA; vendor (NetApp/Dell/VAST) preferred.
RELEVANT EXPERIENCE
Tools / Tech
Source: Larsen & Toubro careers — Read the original posting and apply
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