Full-Time

Senior System Security Test Engineer

Datacenter

Posted on 8/16/2025

NVIDIA

NVIDIA

10,001+ employees

Designs GPUs and AI HPC platforms

Compensation Overview

$148k - $287.5k/yr

+ Equity

Company Historically Provides H1B Sponsorship

Santa Clara, CA, USA

Remote

Category
QA & Testing (1)
Required Skills
Python
Software Testing
Jenkins
C/C++
Requirements
  • B.S./M.S./PHD in Electrical Engineering, Computer Engineering, Computer Science, or related field (or equivalent experience)
  • 5+ years of experience in software/firmware security testing, with a focus on embedded or low-level systems
  • Strong knowledge of system architecture, boot processes, SoCs, I2C/SPI/PCIe interfaces, and embedded controllers
  • Proven experience designing test frameworks and infrastructure in Python, C/C++, or similar languages
  • Hands-on experience with server platforms and debugging
  • Experience with lab automation, HW-in-the-loop testing, and CI/CD pipelines (e.g., Jenkins, GitLab)
  • Strong debugging, problem-solving, and analytical skills
  • Excellent communication and collaboration skills; experience working in a globally distributed team is a plus
Responsibilities
  • Define End-to-End Security Test Strategy: Own and drive the pre-QA system-level test architecture and validation strategy for security across multiple NVIDIA platforms. Develop test plans aligned with customer use cases.
  • Architect Scalable Security Test Infrastructure: Design and implement modular, reusable test frameworks and automation harnesses that support security feature testing. Ensure test infrastructure scales efficiently across multiple systems in parallel.
  • Execute Automated Security Test Plans: Using the scalable automated test infrastructure, implement regular platform-level security test plans focused on validating core security features and functionality.
  • Drive Root Cause Analysis and Debugging: Lead complex issue investigations that span firmware, software, and hardware layers. Develop and document debug methodologies and tools to improve diagnosis efficiency across the team.
  • Engage with Engineering Teams across Functions: Work closely with firmware developers, hardware architects, silicon validation, platform QA, and system software teams to ensure comprehensive security test coverage. Influence early design decisions to optimize testability and automation readiness.
  • Own Security Quality Metrics: Define security quality KPIs such as code coverage, bug escape rate, and validation completeness. Establish dashboards and reporting mechanisms to track progress and drive data-driven decision-making. Partner with engineering and infrastructure teams to enhance test automation pipelines, integrate continuous testing into nightly and pre-merge workflows, and ensure fast and reliable release qualification.
  • Enable Productization and Customer Readiness: Validate real-world use cases, customer configurations, and production scenarios. Contribute to release gates and sign-off criteria to ensure security features are ready for deployment in systems critical to the mission.
  • Mentor, Lead, Explore, and Adopt Emerging Technologies: Foster a culture of quality, innovation, and continuous learning across the organization. Stay up to date on trends in embedded validation, test automation frameworks, and industry standards. Champion the adoption of new tools, methodologies, and best practices to raise the quality bar. Boost Team Efficiency with AI: Demonstrate proven experience using AI-powered tools and copilots to accelerate test development, automate repetitive validation workflows, and streamline debug and root cause analysis.
Desired Qualifications
  • Experience with NVIDIA platforms (e.g., DGX, HGX, Grace Blackwell systems)
  • Exposure to security validation and test focused on features like Attestation and Secure Update
  • Strong understanding of modern data center security features such as Attestation, Secure Boot/Update, and Recovery
  • Prior experience with OpenBMC Test Automation
  • Prior role as a test architect or technical lead for large-scale firmware or embedded validation programs
  • Contributions to open-source testing tools or frameworks with strong knowledge of cloud-scale validation, infrastructure automation, or virtualization
  • Prior experience with using AI tools to design test plan, identify test gaps, automation and failure analysis

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

Simplify Jobs

Simplify's Take

What believers are saying

  • Data centers generate 89% of $215.9B FY2026 revenue.
  • $40B acquisitions like OpenAI bolster AI infrastructure dominance.
  • Nemotron models and Drive Thor accelerate agentic AI adoption.

What critics are saying

  • AMD MI450X outperforms Blackwell by 25% per watt in inference.
  • Huawei Ascend 910D blocks $10B China AI sales due to bans.
  • Google TPU v6 cuts hyperscaler GPU dependency by 60%.

What makes NVIDIA unique

  • NVIDIA invented GPU in 1999, pioneering accelerated computing.
  • CUDA platform from 2006 enables GPUs for AI and HPC.
  • Holds 92% discrete GPU market share as of Q1 2025.

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Benefits

Company Equity

401(k) Company Match

Growth & Insights and Company News

Headcount

6 month growth

-1%

1 year growth

-3%

2 year growth

-2%
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Nvidia and Dell Technologies are positioned as attractive AI infrastructure investments ahead of their May earnings reports, according to recent analysis. Both companies supply critical hardware for AI computing, with demand for AI capacity continuing to outpace available resources across major cloud services. Nvidia shares have remained flat for six months despite strong fundamentals. Last quarter, its data centre business generated $62 billion in revenue, up 75% year over year, with a 75% gross margin. The company expects over $1 trillion in cumulative orders for its Blackwell and upcoming Rubin chips through 2027. Trading at 17 times next year's expected earnings, Nvidia's valuation appears discounted relative to its 66% revenue growth in fiscal year 2026. Dell Technologies similarly stands to benefit from the AI infrastructure build-out. Both companies report earnings in May.

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