Full-Time

Data Center Firmware Test Architect

Posted on 7/12/2025

Deadline 11/21/25
NVIDIA

NVIDIA

10,001+ employees

Designs GPUs and AI HPC platforms

Compensation Overview

$200k - $322k/yr

+ Equity + Benefits

Company Historically Provides H1B Sponsorship

Santa Clara, CA, USA

In Person

Category
QA & Testing (2)
,
Required Skills
Kubernetes
Python
Machine Learning
Jenkins
C/C++
Linux/Unix
Requirements
  • B.S./M.S./PhD in Electrical Engineering, Computer Engineering, Computer Science, or related field
  • 12+ years of experience in software/firmware 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
  • Expertise with platform standards for security, telemetry and manageability (NIST, DMTF)
  • Hands-on experience with server platform, network, storage, cluster configuration and debugging
  • Background with platform telemetry, datacenter node lifecycle management/support including CPU/GPU workloads
  • Proficiency in scripting languages such as Python
  • Expertise in administering, operating, and configuring Kubernetes and Envoy
  • Validated experience in Continuous Integration/Continuous Delivery (CI/CD) tools such as Gitlab and Jenkins and the GitOps model
  • 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 Test Strategy: Own and drive the overall test architecture and validation strategy for firmware across multiple NVIDIA platforms—from pre-silicon simulation and emulation to post-silicon bring-up and production readiness. Develop test plans aligned with product deliverables and customer use cases
  • Architect Scalable Test Infrastructure: Design and implement modular, reusable test frameworks and automation harnesses that support functional, integration, stress, regression, power, security, and performance testing. Ensure test infrastructure scales efficiently across hundreds of systems in parallel
  • Engage with Engineering Teams across Functions: Work closely with firmware developers, hardware architects, silicon validation, platform QA, and system software teams to ensure comprehensive test coverage. Influence early design decisions to optimize testability and automation readiness
  • Own Firmware Quality Metrics: Define quality KPIs such as code coverage, system uptime, bug escape rate, and validation completeness. Establish dashboards and reporting mechanisms to track progress and drive data-driven decision-making
  • 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
  • Innovate in Lab Automation and CI/CD: Partner with DevOps 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 firmware is ready for deployment in systems critical to the mission
  • Mentor, Lead, Explore and Adopt Emerging Technologies: Serve as a technical mentor and coach to firmware QA engineers and junior test developers. 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 Hopper systems)
  • Exposure to security validation, compliance (e.g., FIPS, BMC security), or thermal/power validation
  • 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

  • Agentic AI adoption at scale drives major inflection in inference demand globally.
  • Jensen Huang projects $3T-$4T global AI factory buildout through 2030.
  • Data centre networking revenue surged 263% YoY to $10.98B in Q4 FY2026.

What critics are saying

  • Nemotron 3 open weights enable AMD and Intel to replicate NVIDIA's software moat.
  • Insider selling over three months signals executive doubt about sustaining 73% growth.
  • $30B OpenAI investment exposes NVIDIA to catastrophic losses from governance collapse.

What makes NVIDIA unique

  • Vera Rubin launching July 2026 reduces inference token costs tenfold versus Blackwell.
  • Nemotron 3 Nano Omni achieves 9x higher throughput on consumer hardware like RTX 4090.
  • Clear datacenter product roadmap extends through 2028 with Feynman arriving in 2028.

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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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