採用
福利厚生
•Healthcare
•Parental Leave
•Equity
必須スキル
Python
Apache Spark
TensorFlow
NVIDIA is building the world’s leading AI company, and we are looking for an experienced Cloud Solution Architect to help assist customers with adoption of GPU hardware and Software, as well as building and deploying Machine Learning (ML) , Deep Learning (DL), data analytics solutions on various Cloud Computing Platforms. As part of the Solutions Architecture team, we work with some of the most exciting computing hardware and software technologies including the latest breakthroughs in machine learning and data science. A Solutions Architect is the first line of technical expertise between NVIDIA and our customers so you will engage directly with developers, researchers, and data scientists with some of NVIDIA’s most strategic technology customers as well as work directly with business and engineering teams on product strategy. We are looking for a Solutions Architect to help drive end-to-end technology solutions applying NVIDIA’s full set of technologies based on business needs of customers. Join us in this exciting endeavor!
What you will be doing:
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Working with Cloud Service Providers to develop and demonstrate solutions based on NVIDIA’s ML/DL and data science software and hardware technologies
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Build and deploy AI/ML solutions at scale using NVIDIA's AI software on cloud-based GPU platforms.
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Build custom Po Cs for solution that address customer’s critical business needs applying NVIDIA hardware and software technology
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Partner with Sales Account Managers or Developer Relations Managers to identify and secure new business opportunities for NVIDIA products and solutions for ML/DL and other software solutions
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Prepare and deliver technical content to customers including presentations about purpose-built solutions, workshops about NVIDIA products and solutions, etc.
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Conduct regular technical customer meetings for project/product roadmap, feature discussions, and intro to new technologies. Establish close technical ties to the customer to facilitate rapid resolution of customer issues
What we need to see:
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3+ years of Solutions Engineering (or similar Sales Engineering roles) or equivalent experience
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3+ years of work-related experience in Deep Learning and Machine Learning, including deep learning frameworks Tensor Flow or Py Torch, GPU, and CUDA experience extremely helpful.
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BS/MS/PhD in Electrical/Computer Engineering, Computer Science, Statistics, Physics, or other Engineering fields or equivalent experience.
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Established track record of deploying solutions in cloud computing environments including AWS, GCP, or Azure
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Knowledge of DevOps/ML Ops technologies such as Docker/containers, Kubernetes, data center deployments
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Ability to use at least one scripting language (i.e., Python)
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Good programming and debugging skills
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Ability to communicate your ideas/code clearly through documents, presentation etc.
Ways to stand out from the crowd:
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AWS, GCP or Azure Professional Solution Architect Certification.
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Hands-on experience with NVIDIA GPUs and SDKs (e.g. CUDA, RAPIDS, Triton etc.)
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System-level experience specifically GPU-based systems
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Experience with Deep Learning at scale
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Familiarity with parallel programming and distributed computing platforms
We make extensive use of conferencing tools, but occasional travel is required for local on-site visit to customers and industry events. 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 124,000 USD - 195,500 USD for Level 2, and 152,000 USD - 218,500 USD for Level 3.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until January 20, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering a diverse 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.
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NVIDIAについて

NVIDIA
PublicA computing platform company operating at the intersection of graphics, HPC, and AI.
10,001+
従業員数
Santa Clara
本社所在地
$4.57T
企業価値
レビュー
4.1
10件のレビュー
ワークライフバランス
3.5
報酬
4.2
企業文化
4.3
キャリア
4.5
経営陣
4.0
75%
友人に勧める
良い点
Great culture and supportive environment
Smart colleagues and excellent people
Cutting-edge technology and learning opportunities
改善点
Team-dependent experience and outcomes
Work-life balance issues with long hours
Politics and influence over competence
給与レンジ
73件のデータ
Junior/L3
Mid/L4
Junior/L3 · Analyst
7件のレポート
$170,275
年収総額
基本給
$130,981
ストック
-
ボーナス
-
$155,480
$234,166
面接体験
7件の面接
難易度
3.1
/ 5
体験
ポジティブ 0%
普通 86%
ネガティブ 14%
面接プロセス
1
Application Review
2
Recruiter Screen
3
Online Assessment
4
Technical Interview
5
System Design Interview
6
Team Review
よくある質問
Coding/Algorithm
System Design
Technical Knowledge
Behavioral/STAR
ニュース&話題
Negotiating NVIDIA's Offer
Base, stock, and sign-on negotiable. Recruiters invested in closing candidates. CEO reviews all 42K employee salaries monthly. Stock growth has made many employees millionaires.
News
·
NaNw ago
NVIDIA Company Reviews
WLB rated 3.9/5 (lowest category). 64% satisfied with WLB but 53% feel burnt out. Compensation rated 4.4-4.5/5. Experience highly team-dependent.
News
·
NaNw ago
NVIDIA Interview Discussions
Technical bar is high with 4-6 rounds. Process takes 4-8 weeks. Expect C++ questions, LeetCode medium, and system design. Difficulty rated 3.16/5.
News
·
NaNw ago
NVIDIA Culture Discussions
Team-dependent experience; sink-or-swim culture that rewards high performers but can be overwhelming. No politics, flat structure, but demanding workload with some teams requiring evening/weekend work.
News
·
NaNw ago