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We are now seeking a Senior Infrastructure and Build Systems Engineer for NVIDIA AI TensorRT-LLM team. This is a unique opportunity to take full ownership of the critical systems that power our engineering innovation. You and the team will be responsible for the entire infrastructure/DevOps landscape, from our CI/CD pipelines to our build systems to product security, driving efficiency and reliability across the organization. You will work with autonomy to design and implement the best solutions and collaborate with external partners to achieve our goals. If you're passionate about infrastructure, automation, observability, and compliance, we want you with us at one of the most innovative companies in the world!
What you'll be doing:
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Building and maintaining infrastructure from first principles needed to deliver TensorRT LLM
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Maintain CI/CD pipelines to automate the build, test, and deployment process and build improvements on the bottlenecks. Managing tools and enabling automations for redundant manual workflows via Github Actions, Gitlab, Terraform, etc
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Enable performing scans and handling of security CVEs for infrastructure components
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Improve the modularity of our build systems using CMake
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Use AI to help build automated triaging workflows
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Extensive collaboration with cross-functional teams to integrate pipelines from deep learning frameworks and components is essential to ensuring seamless deployment and inference of deep learning models on our platform.
What we need to see:
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Masters degree or equivalent experience
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3+ years of experience in Computer Science, computer architecture, or related field
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Ability to work in a fast-paced, agile team environment
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Excellent Bash, CI/CD, Python programming and software design skills, including debugging, performance analysis, and test design.
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Experience with CMake.
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Background with Security best practices for releasing libraries.
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Experience in administering, monitoring, and deploying systems and services on GitHub and cloud platforms. Support other technical teams in monitoring operating efficiencies of the platform, and responding as needs arise.
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Highly skilled in Kubernetes and Docker/containerd. Automation expert with hands-on skills in frameworks like Ansible & Terraform. Experience in AWS, Azure or GCP
Ways to stand out from the crowd:
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Experience contributing to a large open-source deep learning community - use of GitHub, bug tracking, branching and merging code, OSS licensing issues handling patches, etc.
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Experience in defining and leading the DevOps strategy (design patterns, reliability and scaling) for a team or organization.
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Experience driving efficiencies in software architecture, creating metrics, implementing infrastructure as code and other automation improvements.
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Deep understanding of test automation infrastructure, framework and test analysis.
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Excellent problem solving abilities spanning multiple software (storage systems, kernels and containers) as well as collaborating within an agile team environment to prioritize deep learning-specific features and capabilities within Triton Inference Server, employing advanced troubleshooting and debugging techniques to resolve complex technical issues.
NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most experienced and hard-working people in the world working for us. Are you creative and autonomous? Do you love a challenge? If so, we want to hear from you. Come help us build the real-time, efficient computing platform driving our success in the dynamic and quickly growing field Deep Learning and Artificial Intelligence.
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until April 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.
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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.
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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.
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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.
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