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Senior Field Applications Engineer, AI Infrastructure Build - Execution

NVIDIA nvidia.com Open · verified Oct 24, 2026
Remote United States Full-time Senior ML Platform & Ops

At a glance

Senior ML Platform & Ops role at NVIDIA. Remote, United States · full-time.

In listing ML Platform & Ops salary

RoleML Platform & Ops
SenioritySenior
LocationUnited States
WorkplaceRemote
EmploymentFull-time
PostedOct 14, 2026 · 10d ago
Role brief

remoteroles summary, based on the employer's posting.

What you'll do

  • Get AI Factory deployments through bring-up and validation, resolving field problems with OEM and deployment partners
  • Lead urgent investigations across servers, GPUs, networking, storage, firmware, Linux, power, and related infrastructure
  • Reproduce blockers, gather evidence, isolate fault domains, and align owners on the next steps
  • Improve diagnostic checks and troubleshooting guidance, then turn deployment lessons into reusable playbooks
  • Keep leaders informed on active risks, obstacles, decisions needed, and recovery plans

What you bring

  • A bachelor's or master's in a relevant engineering or computing discipline, or equivalent experience
  • At least five years supporting data center deployment, rack integration, field or manufacturing support, or similar systems work
  • Hands-on experience diagnosing complex infrastructure faults, including servers, GPUs, storage, firmware, Linux, cabling, or power
  • A record of working directly with partners, customers, OEMs, or deployment teams in field or production settings

Who this fits

This suits a senior, hands-on technical contributor who can troubleshoot in fast-moving deployment settings and communicate clearly with engineering teams and leadership. On-site work is expected during key build and issue windows, with travel of up to fifty percent.

From the employer

NVIDIA is looking for a Senior Field Applications Engineer to assist with AI Factory build implementation and swift assistance alongside OEM and deployment collaborators. This position offers practical, on-site technical support for initial deployments, critical field challenges, preparation shortfalls, and repeated build issues that need focused technical resolution.


You will collaborate with NVIDIA engineering, services, architecture, program, account, field, and partner-facing teams to identify issues, shorten resolution times, validate diagnostic flows, and transform field findings into repeatable guidelines. This role suits a senior technical contributor who can work onsite, provide clarity during critical issues, and help establish a more consistent approach for AI Factory build-outs. This is a field-facing role with encouraged onsite support during critical build, bring-up, validation, and blocking issue windows.


What you'll be doing:

  • Deliver direct field assistance for AI Factory build implementation, encompassing First Time Deployments, deployment bring-up, validation, and issue triage with OEM and deployment partners.
  • Serve as a senior technical resource for urgent field issues involving customer concerns across rack, server, GPU, networking, storage, firmware/BMC, Linux, cabling, power, thermal, and deployment-tooling domains.
  • Deploy to partner or field sites as needed to support targeted rapid response, critical issue closure, and execution risk reduction.
  • Drive structured triage for deployment blockers, including failure reproduction, data collection, domain isolation, quality of critical issue packets, and owner alignment.
  • Help reduce time to resolution by validating diagnostic flows, improving test practices, and detailing repeatable troubleshooting methods.
  • Support bone-pile review and reduction by helping classify failures, identify repeat patterns, and connect field data to root cause and corrective actions.
  • Capture First Time Deployment lessons learned and update guidelines, readiness criteria, and execution playbooks for reuse across OEM engagements.
  • Provide concise leadership access to issue status, risk, blockers, decision needs, and recovery plans during active deployments.

What we need to see:

  • Bachelor's or Master's degree in Electrical Engineering, Computer Engineering, Computer Science, Systems Engineering, or a related technical field (or equivalent experience).
  • 5+ years of experience in data center deployment, rack integration, technical field support, manufacturing support, partner services, infrastructure bring-up, or large-scale systems troubleshooting.
  • Practical experience troubleshooting intricate infrastructure problems related to servers, GPUs, switches, storage, firmware/BMC, Linux, cabling, optics, power, thermal, or deployment tooling.
  • Experience working directly with partner, customer, OEM, ODM, system integrator, or deployment services teams in field or production environments.
  • Strong troubleshooting in the field, including rigorous debug, clean data collection, reproduction quality, and clear handoff of critical issues.
  • Ability to operate onsite in fast-paced deployment environments while communicating clearly with engineering, field teams, partner teams, and leadership.
  • Strong written and verbal communication skills, including the ability to summarize complex technical issues into executive-ready status and risk updates.
  • Travel required (up to 50%) to support field engagements, partner sites, and deployment activities.

Ways to stand out from the crowd:

  • Experience with AI Factory, accelerated computing, rack-scale AI infrastructure, large-scale GPU systems, or HPC deployments.
  • Background with NVIDIA GPUs, NVIDIA networking, InfiniBand, RoCE, high-speed Ethernet, or large-scale cluster bring-up.
  • Experience crafting or improving diagnostic flows, test procedures, readiness playbooks, blocking issue templates, or best-practice libraries.
  • Experience with bone-pile analysis, RMA/failure pattern review, root cause feedback loops, or systemic quality improvement.
  • Strong Linux, scripting, automation, telemetry, or log-analysis skills.

NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative and autonomous, we want to hear from you!

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 for Level 3, and 160,000 USD - 253,000 USD for Level 4.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until October 18, 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.

Opportunity

ML Platform & Ops work from LinkedIn, X, Reddit and Upwork, in one list.

Each morning you get everything that fits, strongest first.

ML Platform & OpsRemote

Find me work

By the team behind remoteroles.

Find me work
Opportunity

ML Platform & Ops work from LinkedIn, X, Reddit and Upwork, in one list.

Each morning you get everything that fits, strongest first.

Find me work

By the team behind remoteroles.