Field Application Engineer
We are currently seeking a Field Applications Engineer focused on production at scale to join our dedicated and hardworking team. At NVIDIA, we are leading the AI computing revolution, creating innovative deep learning solutions that are transforming industries globally. As a member of our team, you will play a vital role in ensuring the reliability, manufacturability, and quality of our GPU products across production and deployment environments. If you have a strong passion for root cause analysis, yield improvement, and working with cross-functional engineering teams, this is an excellent opportunity for you to make a meaningful contribution!
What you'll be doing:
- Be a technical specialist on GPU and networking products, directly supporting manufacturing, quality, and failure analysis teams to improve product reliability and yield.
- Actively 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/process improvements.
- Frequent on-site presence in labs or manufacturing sites to diagnose, reproduce, and resolve hardware and system-level failures.
- Support the product lifecycle from NPI (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 strong communication channels and collaborative relationships with cross-functional teams (design, validation, manufacturing and quality) to drive issue resolution, root cause determination, and corrective actions.
What we need to see:
- BS or MS in Engineering, Electrical Engineering, Physics, or Computer Science (or equivalent experience).
- 5+ years of work-related experience in the high-tech electronics industry, particularly in manufacturing, failure analysis, validation, or hardware debug roles.
- Capable of excelling in a dynamic, constantly evolving environment.
- Strong ability to manage multiple failure investigations, escalations, and yield improvement initiatives.
- Expert 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, with the ability to clearly present failure analysis results and collaborate effectively with cross-functional engineering teams and management.
Ways to stand out from the crowd:
- Experience with ARM and NVIDIA GPU development.
- Knowledge of Embedded Linux Systems, APIs, and system-level debugging tools for root cause analysis.
- Experience working with manufacturing partners, ODMs/OEMs, or reliability/quality teams in high-volume production environments.
- In-depth understanding of CPU/GPU architecture and system-level failure mechanisms.
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 132,000 USD - 207,000 USD.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until October 5, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
About NVIDIA
NVIDIA is a computing platform company operating at the intersection of graphics, HPC, and AI.
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