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NVIDIA

Designs the chips and software that power AI

Field Application Engineer

Solution EngineeringConfirmed live in the last 24 hours
Full-time

About the Job

Requirements

  • A BS or MS in Engineering, Electrical Engineering, Physics, or Computer Science, or equivalent experience.
  • At least 4 years of work-related experience in the high-tech electronics industry, particularly in manufacturing, failure analysis, validation, or hardware debugging.
  • Ability to manage multiple failure investigations, escalations, and yield-improvement initiatives.
  • Strong analytical and problem-solving abilities.
  • Strong time-management and organizational skills for coordinating complex failure analysis and cross-functional investigations.
  • Excellent written and oral communication skills in English, including presenting failure-analysis results and collaborating with engineering teams and management.

Responsibilities

  • Serve as a technical specialist on GPU and networking products, supporting manufacturing, quality, and failure-analysis teams to improve product reliability and yield.
  • Establish and nurture technical relationships with internal engineering teams, manufacturing partners, and quality teams.
  • Identify system failure modes, manufacturing risks, and product requirements to drive corrective actions and design and process improvements.
  • Be frequently present on-site in labs or manufacturing sites to diagnose, reproduce, and resolve hardware and system-level failures.
  • Support the product lifecycle from New Product Introduction through high-volume manufacturing and field returns, ensuring quality, reliability, and continuous improvement.
  • Develop failure-analysis methodologies, test plans, and diagnostic tools for hardware validation.
  • Provide technical training and documentation to manufacturing, test, and quality teams on failure modes and debugging techniques.
  • Establish communication channels and collaborative relationships with design, validation, manufacturing, and quality teams to drive issue resolution, root-cause determination, and corrective actions.

Desired Qualifications

  • Experience with ARM and NVIDIA GPU development.
  • Knowledge of embedded Linux systems, application programming interfaces, and system-level debugging tools for root-cause analysis.
  • Experience working with manufacturing partners, original design manufacturers, original equipment manufacturers, or reliability and quality teams in high-volume production environments.
  • In-depth understanding of central processing unit and graphics processing unit architecture and system-level failure mechanisms.

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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