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NVIDIA

Designs the chips and software that power AI

Senior MGX Ecosystem Engineer

Hardware Systems IntegrationConfirmed live in the last 24 hours
Full-time

About the Job

Requirements

  • A bachelor’s degree in Electrical Engineering, Mechanical Engineering, Thermal Engineering, Computer Engineering, or a related technical field, or equivalent experience.
  • At least 6 years of demonstrated ability in hardware platform engineering, systems engineering, ecosystem engineering, or technical partner management.
  • Solid knowledge of server, data center, AI infrastructure, networking, storage, or high-performance computing platforms.
  • Demonstrated expertise in at least two of electrical, mechanical, and thermal engineering, and working knowledge of all three.
  • Solid grasp of the hardware development lifecycle from initial concept through mass production.
  • Ability to travel domestically and internationally up to 25–40%.

Responsibilities

  • Serve as the primary technical interface to MGX and ecosystem partners, including original equipment manufacturers, original design manufacturers, and component suppliers.
  • Drive ecosystem growth by enabling partners to develop high-performance hardware solutions based on MGX platform specifications.
  • Lead technical discussions, product reviews, and ecosystem readiness assessments.
  • Provide system-level engineering expertise spanning electrical, mechanical, and thermal domains.
  • Support integration of compute, networking, power delivery, cooling, and mechanical subsystems.
  • Define and accomplish validation strategies for ecosystem hardware solutions.
  • Deliver technical training, workshops, and onboarding programs for ecosystem partners.
  • Collaborate with product management, engineering, operations, manufacturing, and business development teams.

Desired Qualifications

  • A master’s degree or equivalent experience in Engineering or a related technical field.
  • Experience with AI server platforms, GPU-based systems, high-density compute infrastructure, or hyperscale data center deployments.
  • Familiarity with thermal simulation tools, computer-aided design platforms, and hardware validation methodologies.
  • Experience with liquid cooling technologies and rack-level cooling architectures.
  • Understanding of industry standards and certifications related to server and data center infrastructure.

About the Company

NVIDIA

Designs the chips and software that power AI

NVIDIA designs the chips and software that power artificial intelligence and sells complete data center systems to cloud providers, AI labs, and other businesses, along with GeForce graphics cards for gamers. Its GPUs, chips that perform thousands of calculations at once, became the main hardware for AI after researchers used them to train the AlexNet image-recognition model in 2012. NVIDIA connects many GPUs with its own processors and networking gear into servers and rack-sized computers, and developers program them through its CUDA software. These systems bring in most of its sales, and it also makes chips for cars and robots. Jensen Huang co-founded NVIDIA in 1993, and it is based in Santa Clara, California.

Company size
10,001+
Company stage
IPO
Headquarters
Santa Clara, CA
Founded
1993

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