Full-Time

Senior Storage Software Engineer

DGXC Data Services

Deadline 8/18/26
NVIDIA

NVIDIA

10,001+ employees

Designs GPUs and AI HPC platforms

Compensation Overview

$152k - $287.5k/yr

+ Equity

Company Historically Provides H1B Sponsorship

Remote in USA + 5 more

More locations: Washington, USA | California, USA | Texas, USA | Santa Clara, CA, USA | North Carolina, USA

Hybrid

The posting includes a Santa Clara in-person option and remote options in the listed U.S. locations.

Bachelor's

Category
Software Engineering (1)
Required Skills
Kubernetes
Rust
Python
Distributed Systems
Data Structures & Algorithms
Java
Operating Systems
Data Engineering
Go
Observability
C/C++
Linux/Unix

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Requirements
  • A Bachelor of Science degree in Computer Science, Information Systems, or Computer Engineering, or equivalent experience, is required.
  • At least 5 years of software engineering experience is required.
  • Strong foundations in algorithms, data structures, distributed systems, operating systems, and practical software design are required.
  • Experience building performance-sensitive systems, storage, backend, or cloud-native software in Go, Python, Rust, C, C++, or Java is required.
  • Experience with storage systems, object stores, caching, Linux systems, Kubernetes, or cloud infrastructure is required.
  • Ability to reason about performance, scalability, concurrency, reliability, and operational tradeoffs in production systems is required.
  • Ability to design APIs, document systems, communicate clearly, and break ambiguous infrastructure problems into practical execution plans is required.
  • Practical judgment around AI-assisted or agentic engineering workflows, including using clear intent, specifications, acceptance criteria, tests, and verification to guide development, is required.
Responsibilities
  • Build storage technologies, client libraries, and filesystem frameworks that enable AI workloads to access data across object stores, file systems, and hybrid cloud infrastructure.
  • Develop high-performance storage paths for training and inference workflows, including data loading, checkpointing, caching, POSIX-style access, and object-store integration.
  • Build observability systems that diagnose storage bottlenecks, attribute GPU idle time to input/output behavior, and expose actionable telemetry through production monitoring stacks.
  • Improve the performance, scalability, and reliability of storage systems serving massive datasets, deep directory trees, and high-concurrency AI workloads.
  • Work with internal AI teams, platform teams, site reliability engineering, and operations to validate storage behavior against real workloads and production environments.
  • Use modern software engineering practices, including AI-assisted and agentic development workflows, while maintaining high standards for design, testing, security, performance, and verification.
Desired Qualifications
  • Background with Linux kernel observability, eBPF, tracing, or low-overhead telemetry systems.
  • Experience with FUSE, POSIX filesystems, object-store-backed filesystems, or filesystem metadata and indexing.
  • Experience optimizing storage performance for AI training, checkpointing, inference, or large-scale data pipelines.

NVIDIA designs and manufactures graphics processing units (GPUs) and computing platforms used for gaming, data centers, and artificial intelligence. These products work by using parallel processing to handle complex mathematical calculations much faster than standard computer processors, supported by a software ecosystem that allows developers to build and run AI models. Unlike competitors that may focus solely on hardware, NVIDIA integrates its chips with specialized software and cloud services to create a complete environment for high-performance tasks. The company’s goal is to provide the underlying technology necessary to power advanced computing, from realistic video game graphics to autonomous vehicles and large-scale data analysis.

Company Size

10,001+

Company Stage

IPO

Headquarters

Santa Clara, California

Founded

1993

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Simplify Jobs

Simplify's Take

What believers are saying

  • NVIDIA’s August 10, 2026 financing platforms target over $500 billion for AI infrastructure.
  • Vera Rubin production shipments start this fall, creating a fresh upgrade cycle by 2027.
  • SB Energy’s Ohio campus guarantees exclusive NVIDIA AI compute, securing power-constrained demand.

What critics are saying

  • U.S. export controls keep NVIDIA shut out of China’s largest advanced-AI chip market.
  • Commerce tightened overseas-subsidiary rules on May 31, 2026, crushing workaround sales channels.
  • AMD MI350 and future MI450 racks directly attack NVIDIA pricing and platform leadership in 2026.

What makes NVIDIA unique

  • NVIDIA shipped Vera Rubin into full production by May 31, 2026, ahead of rivals.
  • Blackwell and Rubin plus CUDA lock developers into NVIDIA’s hardware-software stack.
  • August 10, 2026 partnerships with Apollo, BlackRock, and KKR turn compute into finance.

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Benefits

Company Equity

401(k) Company Match

Growth & Insights and Company News

Headcount

6 month growth

0%

1 year growth

-2%

2 year growth

-3%
Yahoo Finance
Aug 23rd, 2026
Cramer: Nvidia doesn't need anyone but Elon Musk as biggest chip buyer

CNBC host Jim Cramer expressed continued confidence in Nvidia despite the stock's modest 13.7% year-to-date gain in 2026. He suggested the chipmaker doesn't need to invest in AI companies anymore, believing Elon Musk will become its biggest customer. Cramer predicted Musk could purchase Nvidia's entire Vera Rubin production. However, concerns persist about AI spending sustainability, with UBS projecting hyperscaler capital expenditure growth could slow to 25% in 2027 and 6% in 2028. Nvidia's Q1 fiscal 2027 results showed data centre revenue jumping 92% annually to $75 billion, with 75% gross margins. The company guided Q2 revenue to $91 billion, exceeding analyst estimates of $86.84 billion. Bulls project earnings per share could exceed $15 in 2027 and $20 in 2028.

Yahoo Finance
Aug 22nd, 2026
Nvidia partners with Blackstone and 5 firms to mobilise $500B for AI infrastructure

NVIDIA announced partnerships with Blackstone, Apollo, BlackRock, Brookfield, Goldman Sachs and KKR in August 2026 to create AI compute financing platforms targeting over $500 billion in third-party capital for AI infrastructure. Final agreements remain pending. The same month, Blackstone was reportedly evaluating a potential $1.50 billion to $2.00 billion acquisition of Indian renewables platform Blupine Energy from Actis. The moves highlight Blackstone's focus on digital infrastructure and energy transition assets. Analysts note the NVIDIA partnership aligns with Blackstone's existing data centre and private credit commitments, potentially deepening its AI infrastructure financing role. However, concerns about interest rates, deal flow, and market volatility persist. Blackstone's narrative projects $22.5 billion revenue and $9.8 billion earnings by 2029.

Yahoo Finance
Aug 22nd, 2026
Whale Rock dumps 64% of Nvidia stake, shifts $1.5M into AMD shares

Whale Rock Capital Management slashed its Nvidia stake by approximately 64% in the second quarter, reducing its position from 1.04 million shares to 377,204 shares, according to the hedge fund's latest 13F filing. The move appears to be a portfolio rebalancing rather than a retreat from AI semiconductors. During the same period, Whale Rock dramatically increased its Advanced Micro Devices holdings from 69,211 shares to roughly 1.51 million shares, whilst also reducing its Broadcom stake. Nvidia, which designs GPUs and accelerated computing platforms for AI infrastructure, currently trades near $215 per share with a market capitalisation of $5.24 trillion. The company recently reported quarterly revenue growth of 85% year-over-year. The stock trades at a forward price-to-earnings multiple of 25.2 times.

Yahoo Finance
Aug 21st, 2026
Nvidia dominates AI chip market with $75B data center revenue, dwarfing AMD and Qualcomm

Nvidia continues to dominate the AI chip market despite competition from Advanced Micro Devices and Qualcomm, according to recent data. The company's data centre revenue reached $75.2 billion in the first quarter of fiscal 2027, growing 92% year over year. By comparison, AMD's data centre revenue totalled $6.7 billion in its most recent quarter, whilst Qualcomm is targeting $15 billion in data centre revenue by fiscal 2029. Nvidia controls an estimated 74% of the AI inference chip market and holds 80% to 90% of the overall AI chip market, according to Silicon Analysts. With the AI chip market expected to reach $2 trillion by 2030, Nvidia's dominant position suggests significant long-term growth potential.

Toscale
Aug 21st, 2026
Nvidia pays $7B for Poolside's Model Factory in licensing deal that avoids acquisition scrutiny

Nvidia has paid $7 billion for a non-exclusive licence to Poolside AI's Model Factory system and taken a minority stake in the company, according to reports from Newcomer, Bloomberg, and The Information. The deal includes a $6 billion licensing fee and a $1 billion investment at a $12 billion pre-money valuation. The transaction follows similar arrangements with Groq ($20 billion) and Enfabrica ($900 million). By structuring deals as licensing agreements rather than acquisitions, Nvidia avoids antitrust scrutiny whilst securing access to critical AI infrastructure and talent. In this case, 109 Poolside employees are transferring to Nvidia, though co-founders Jason Warner and Eiso Kant remain to lead the independent entity. Poolside's existing investors, including Bain Capital Ventures, eBay, and Citi Ventures, are expected to receive the $6 billion licensing payment by end-2027.