Senior Systems Software Engineer - HPC and AI Storage

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SeniorZdalnie·WarszawaFull-time

#476991·Dodano 5 dni temu·19

Źródło: NVIDIA

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Tech Stack / Keywords

LustreNFSLinux C Pythonshell scriptingLinux VFSRDMAGPUDirect StorageHPC

Podsumowanie oferty

Join the Applied Systems Engineering team to improve storage systems for HPC and AI clusters. You will analyze workloads, develop software fixes, and integrate storage on next-generation NVIDIA platforms using technologies including Lustre, NFS, and Linux.

Wymagania

Deep engineering experience with Lustre, NFS, or comparable shared storage systems, including implementation-level debugging in at least one stack and experience integrating storage into Linux clusters.
Strong C programming and Linux debugging skills, with experience reading, modifying, and diagnosing kernel or user-space storage software.
Understanding of filesystem and distributed-system behavior, including metadata operations, caching and consistency, locking, concurrency, client/server communication, and recovery.
Experience analyzing application access patterns and tuning filesystem or storage-stack behavior to deliver performance improvements.
Ability to take a complex performance or correctness problem from initial symptoms through reproduction, root-cause analysis, implementation, and validation.
Proficiency in Python and shell scripting to build maintainable diagnostic, test automation, and analysis tools.
Ability to independently lead technical efforts, influence design decisions across teams, and communicate findings and tradeoffs clearly.
BS or MS in Computer Science, Engineering, Mathematics, Physics, or equivalent practical experience, with 12+ years of relevant experience.

Nice to have:

Contributions to Lustre, Linux filesystems, NFS implementations, or other storage projects, including features, performance improvements, bug fixes, or technical reviews.
Expertise in Lustre metadata and client I/O, Linux VFS and page cache, NFS protocol and client/server internals, or distributed locking and recovery.
Experience with hierarchical storage management, policy engines, or migration between filesystems and object storage, including data recall and recovery from interrupted transfers.
Experience with RDMA storage transports, GPUDirect Storage, or optimizing data loading and checkpointing for GPU workloads.
Experience with storage security and multi-tenancy, including authentication, identity mapping, permissions, and encryption.

Obowiązki

Engineer and integrate storage systems for large-scale HPC and AI clusters, including Lustre, NFS, and their interaction with compute nodes, networks, and storage hardware.
Examine performance and reliability issues throughout the I/O stack, supervising application behavior across filesystem clients, Linux kernel paths, network protocols, servers, and storage devices.
Develop software fixes and performance improvements, working with NVIDIA engineering teams, storage partners, and open-source maintainers to bring changes through review, testing, and deployment.
Characterize real application I/O, including training-data access, checkpoint and restart, metadata-intensive operations, and concurrent workloads. Translate findings into improvements to software, system configuration, and design.
Build reproducible benchmarks, diagnostic tools, and regression tests that measure efficiency, latency, metadata performance, scalability, and behavior under contention.
Lead storage qualification and commissioning, validating functionality, data integrity, failure recovery, and sustained performance at cluster scale.
Define and implement storage placement, caching, and data lifecycle policies informed by workload requirements, capacity, and operational evidence.

NVIDIA

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