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首次部署经理 - NVIS

雇主

NVIDIA

地点

Santa Clara · 美国

待遇

$面议

工作模式

线下

截止日期

1月10日

福利
Equity,Benefits

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岗位摘要

Lead a team to operationalize NVIDIA's latest GPU and AI networking technologies, driving deployment

岗位职责

Will you be part of the team that helps our partners to develop customer solutions using the latest
NVIDIA full stack accelerated computing platform?
NVIDIA defines and delivers the computing infrastructure of today and tomorrow.
We are committed that these infrastructures deliver the highest value to our customers who own and operate these infrastructures.
We are looking for a team leader to operationalize the latest technologies at
NVIDIA by bridging the gap between prototype models and production-ready deployment plans.
The team will drive initial deployment setup, prepares sites, establishes product feedback loops to design engineering teams, assembles validation data, resolves obstacles, applies workarounds, and details deployment plans.
They lead all aspects of making the latest
NVIDIA products and systems functional by capturing install and bring-up evidence, handle the validation process, describe blockers, and find solutions to deploy AI Factories globally.
What you will be doing:
• Recruit & manage a team of solutions architects, system/network and software engineers focused on large-scale GPU and AI networking deployments.
• Set priorities, allocate resources, mentor, and ensure high-quality customer delivery across multiple concurrent projects - while remaining directly involved in key technical reviews, design decisions, and critical debug efforts.
• Provide deep subject-matter expertise in advanced GPU and network systems and serve as the senior technical point of contact for strategic customers.
• Personally lead and guide complex compute/network configuration and performance debugging, working side-by-side with your team to deliver performant, reliable clusters.
• Guide your team as they lead network / compute / software architecture discussions, and support server, network, and cluster bring-up, including on-site data center work where needed.
• Systematically collect and synthesize customer-specific requirements across your portfolio.
• Partner with GPU/Network Systems Engineering, Product Management, and Sales to influence roadmap priorities and packaging of reference designs and solutions.
• Demonstrate SME in advanced GPU & network systems and be a trusted technical advisor to NVIDIA's strategic customers.
Bring customer-specific requirements to product teams to guide product roadmap features.
• Identify new project opportunities for
NVIDIA products and technology solutions in data center and AI applications.
Work closely with the GPU/Network Systems Engineering, Product management and Sales teams What we need to see:
• BS/MS/PhD in Electrical/Computer Engineering, Computer Science, Physics, or other Engineering fields or equivalent experience.
• 8
overall years in Systems/Solutions/Field Engineering, Network or Data Center Engineering, or similar roles, with 2
years leading or mentoring engineers or architects (formal manager or strong tech lead).
• System-level expertise across
CPU/GPU server architecture, NICs, Linux, system software, and kernel drivers.
• Experience with data center networking (Ethernet and/or InfiniBand switches, fabrics, and associated tooling) and familiarity with data center infrastructure (power, cooling, deployment constraints).
• Proven ability to lead technical teams, set priorities, and drive complex projects from design through production.
• Demonstrated success working with Product Management, Sales, and Engineering.
• Strong time management skills and ability to balance planning with hands-on support where needed.
• Excellent written and verbal communication, including the ability to lead customer meetings, communicate status and risks, and produce clear design docs, debug summaries, and presentations.
Ways to stand out from the crowd:
• Direct people management & recruiting experience for geographically distributed technical teams.
• Track record leading bring-up and deployment of large clusters or supercomputing environments.
• Background in external customer-facing roles (field engineering, escalations, or pre/post-sales architecture).
• Systems engineering, coding, and debugging skills including experience with C/C, Linux kernel and drivers • Hands-on experience with
NVIDIA GPU systems and SDKs (e.g., CUDA),
NVIDIA networking technologies (NICs, RoCE, InfiniBand), and/or ARM-based CPU solutions as well as familiarity with virtualization and cloud-native networking concepts.
We make extensive use of conferencing tools, but occasional (30%) travel is required for on-site visit to customers and industry events.
We are open to remote work location and look forward to have you join our team!
#BuildTheAIFactory Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.
The base salary range is 184,000 USD - 287,500 USD for Level 3, and 216,000 USD - 345,000 USD for Level 4.
You will also be eligible for equity and benefits. Applications for this job will be accepted at least until October 3, 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.

申请条件

BS/MS/PhD in Electrical/Computer Engineering, Computer Science, Physics, or other Engineering fields, or equivalent experience.
8+ overall years in Systems/Solutions/Field Engineering, Network or Data Center Engineering, or similar roles, with 2+ years leading or mentoring engineers or architects (

雇主简介

NVIDIA is a technology company that designs GPUs and system-on-chip units for gaming, professional visualization, data centers, and automotive markets. The Physics Simulation Team focuses on physics simulation for robotics learning and evaluation.

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