Senior Field Application Engineer
This is the employer's own posting, not a copy on a job board.
What we know
Is it still open?
Confirmed still open
Last checked 1h ago — checked against the employer's own applicant tracking system, which is the company answering directly.
We re-read the employer's own applicant tracking system and the posting was still there. That is the company answering directly.
How old is it?
Posted 22h ago
The date the source published, not the day we noticed it (2026-10-02). Last seen at its source 1h ago.
Is it remote?
Mexico, Remote
That is the location the employer filed this posting under. Quoted as written — we do not re-word the source's own location.
Who may apply?
Mexico
The description states no restriction of its own. This is the source's own tag.
Pay not stated
Similar roles pay $93.8k–155.2k/yr
Middle 50% of 11 listings that do state pay — Engineering · all levels · Mexico · USD/year. This employer has published no salary; this is what comparable listings we hold disclose, never converted between currencies or periods. How this is calculated.
Skills named in the ad
Recognised terms only, from a fixed vocabulary — this is what CV matching compares against.
Carried by 1 source
-
workday employer's own board first seen 1h ago · last seen 1h ago
The listing
We are currently seeking a Senior 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!
Local to Guadalajara is strongly preferred.
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.