5 days ago

Senior Storage Software Engineer - DGX Cloud

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 22 hours agoStatus: Live

Job Summary

Build and lead foundational storage software for NVIDIA GPU clusters powering large-scale AI training and inference. Contribute to open-source parallel/distributed file systems and distributed object storage, write and review production code, and diagnose complex storage issues across tens of thousands of GPUs. Validate architecture with scale tests and benchmarks, define performance/tuning guidelines, and partner across AI, SRE, networking, security, and cloud/storage vendors to improve durability, recovery, and GPU availability.

Location: Santa Clara, United States

Workplace: Remote

Employment Type: Full time

Job Function: Software Engineering

Seniority: Mid level

Key Responsibilities

•Contribute code to open-source parallel/distributed file systems and distributed object storage, including upstream fixes/features and direct engagement with maintainers.
•Serve as a hands-on storage software lead by writing/reviewing production code and making final technical decisions on storage deliveries against measurable targets.
•Triage, troubleshoot, and root-cause large storage incidents across very large GPU clusters, covering I/O/metadata performance, data corruption, and recovery.
•Validate storage architecture, capabilities, performance, and durability using scale tests, benchmarks, and recovery drills.
•Define and recommend configuration, tuning, and operational best practices for high-performance file systems on GPU infrastructure and support operators/internal customers.

Pay and Benefits

Salary: USD 224,000 - 431,250 annually

Equity and Bonus:Equity

Key Requirements

•BS, MS, or PhD in Computer Science, Electrical Engineering, or a related field, or equivalent experience.
•Over 12 years of direct storage software engineering experience, including high-performance parallel/distributed file systems at multi-petabyte scale.
•Contributions to open-source distributed or parallel file system projects, with hands-on code writing/review and upstream engagement.
•Experience diagnosing and resolving storage problems in GPU or HPC clusters, including I/O and metadata performance analysis.
•Strong proficiency in at least one systems language (C, C++, Rust, or Go) and proficiency in Python; familiarity with Linux kernel storage/networking stacks and working knowledge of object and block storage.

Experience:12+ yearsOpen sourceDistributed systemsParallel computingHPCAI infrastructureGPU computing

Education:

Skills:CommunicationTroubleshootingRoot-cause analysisHands-on engineeringCollaboration

Tech Stack:CC++RustGoPythonLinux kernelNFSNVMe-oFSPDKRDMARoCEInfiniBandNVMePage cacheVFSMultipathObject storageS3SwiftBlock storage

Company Brief

NVIDIA

Designs and manufactures GPUs, AI accelerators, and system-on-chip products for gaming, data centers, professional visualization, and automotive markets, enabling advanced graphics, AI, and high-performance computing solutions worldwide.

Industry: Electronics Manufacturing

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Santa Clara, United States

Founded: 1993

Glassdoor: 4.3

Website LinkedIn Glassdoor

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NVIDIA

5 days ago

Senior Storage Software Engineer - DGX Cloud

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 22 hours agoStatus: Live

Job Summary

Location: Santa Clara, United States

Workplace: Remote

Employment Type: Full time

Job Function: Software Engineering

Seniority: Mid level

Key Responsibilities

•Contribute code to open-source parallel/distributed file systems and distributed object storage, including upstream fixes/features and direct engagement with maintainers.
•Serve as a hands-on storage software lead by writing/reviewing production code and making final technical decisions on storage deliveries against measurable targets.
•Triage, troubleshoot, and root-cause large storage incidents across very large GPU clusters, covering I/O/metadata performance, data corruption, and recovery.
•Validate storage architecture, capabilities, performance, and durability using scale tests, benchmarks, and recovery drills.
•Define and recommend configuration, tuning, and operational best practices for high-performance file systems on GPU infrastructure and support operators/internal customers.

Pay and Benefits

Salary: USD 224,000 - 431,250 annually

Equity and Bonus:Equity

Key Requirements

•BS, MS, or PhD in Computer Science, Electrical Engineering, or a related field, or equivalent experience.
•Over 12 years of direct storage software engineering experience, including high-performance parallel/distributed file systems at multi-petabyte scale.
•Contributions to open-source distributed or parallel file system projects, with hands-on code writing/review and upstream engagement.
•Experience diagnosing and resolving storage problems in GPU or HPC clusters, including I/O and metadata performance analysis.
•Strong proficiency in at least one systems language (C, C++, Rust, or Go) and proficiency in Python; familiarity with Linux kernel storage/networking stacks and working knowledge of object and block storage.

Experience:12+ yearsOpen sourceDistributed systemsParallel computingHPCAI infrastructureGPU computing

Education:

Skills:CommunicationTroubleshootingRoot-cause analysisHands-on engineeringCollaboration

Tech Stack:CC++RustGoPythonLinux kernelNFSNVMe-oFSPDKRDMARoCEInfiniBandNVMePage cacheVFSMultipathObject storageS3SwiftBlock storage

Company Brief

NVIDIA

Industry: Electronics Manufacturing

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Santa Clara, United States

Founded: 1993

Glassdoor: 4.3

Website LinkedIn Glassdoor