NVIDIA

2 weeks ago

Senior Storage Software Engineer, DGXC Data Services

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI

Last checked: 20 hours agoStatus: Live

Job Summary

Build cloud-native storage technologies and filesystem frameworks that help AI workloads access data across object stores, file systems, and hybrid cloud. Develop high-performance training and inference storage paths for data loading, checkpointing, caching, POSIX-style access, and object-store integration. Create observability systems to diagnose storage bottlenecks and expose actionable telemetry. Collaborate with AI, platform, SRE, and operations teams to validate reliability and performance in production.

Location: Santa Clara, North Carolina, Texas, Washington, California

Workplace: Hybrid

Employment Type: Full time

Job Function: Software Engineering

Seniority: Mid level

Key Responsibilities

•Build storage technologies, client libraries, and filesystem frameworks for AI workloads across object stores, file systems, and hybrid cloud infrastructure.
•Develop high-performance storage paths for training and inference, including data loading, checkpointing, caching, POSIX-style access, and object-store integration.
•Build observability systems to diagnose storage bottlenecks, attribute GPU idle time to I/O behavior, and surface telemetry in production monitoring.
•Improve storage performance, scalability, and reliability for massive datasets and high-concurrency AI workloads.
•Collaborate with internal AI teams, platform teams, SRE, and operations to validate storage behavior against real workloads and production environments.

Pay and Benefits

Salary: USD 152,000 - 287,500 annually

Equity and Bonus:Equity

Key Requirements

•BS in Computer Science, Information Systems, Computer Engineering (or equivalent) and 5+ years of software engineering experience.
•Strong foundation in algorithms, data structures, distributed systems, and operating systems with practical software design.
•Experience building performance-sensitive systems and storage/backend/cloud-native software in Go, Python, Rust, C/C++, or Java.
•Experience with storage systems, object stores, caching, Linux systems, Kubernetes, or cloud infrastructure.
•Ability to reason about performance, scalability, concurrency, reliability, and operational tradeoffs in production systems.

Experience:5+ yearsCloud-nativeStorage systemsDistributed systemsAI infrastructureHybrid cloudObject storageKubernetes

Education:Bachelor's in Computer Science, Information Systems, Computer Engineering (or equivalent)

Skills:CommunicationProblem-solvingDesign and testing disciplinePerformance reasoningPractical judgment

Tech Stack:GoPythonRustCC++JavaLinuxKubernetesEBPFPOSIXFUSEObject storesFilesystemAPIsObservabilityTracing

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

2 weeks ago

Senior Storage Software Engineer, DGXC Data Services

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI

Last checked: 20 hours agoStatus: Live

Job Summary

Location: Santa Clara, North Carolina, Texas, Washington, California

Workplace: Hybrid

Employment Type: Full time

Job Function: Software Engineering

Seniority: Mid level

Key Responsibilities

•Build storage technologies, client libraries, and filesystem frameworks for AI workloads across object stores, file systems, and hybrid cloud infrastructure.
•Develop high-performance storage paths for training and inference, including data loading, checkpointing, caching, POSIX-style access, and object-store integration.
•Build observability systems to diagnose storage bottlenecks, attribute GPU idle time to I/O behavior, and surface telemetry in production monitoring.
•Improve storage performance, scalability, and reliability for massive datasets and high-concurrency AI workloads.
•Collaborate with internal AI teams, platform teams, SRE, and operations to validate storage behavior against real workloads and production environments.

Pay and Benefits

Salary: USD 152,000 - 287,500 annually

Equity and Bonus:Equity

Key Requirements

•BS in Computer Science, Information Systems, Computer Engineering (or equivalent) and 5+ years of software engineering experience.
•Strong foundation in algorithms, data structures, distributed systems, and operating systems with practical software design.
•Experience building performance-sensitive systems and storage/backend/cloud-native software in Go, Python, Rust, C/C++, or Java.
•Experience with storage systems, object stores, caching, Linux systems, Kubernetes, or cloud infrastructure.
•Ability to reason about performance, scalability, concurrency, reliability, and operational tradeoffs in production systems.

Experience:5+ yearsCloud-nativeStorage systemsDistributed systemsAI infrastructureHybrid cloudObject storageKubernetes

Education:Bachelor's in Computer Science, Information Systems, Computer Engineering (or equivalent)

Skills:CommunicationProblem-solvingDesign and testing disciplinePerformance reasoningPractical judgment

Tech Stack:GoPythonRustCC++JavaLinuxKubernetesEBPFPOSIXFUSEObject storesFilesystemAPIsObservabilityTracing

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