採用
福利厚生
•Equity
必須スキル
C++
Python
Go
Distributed systems
Data management
Orchestration
NVIDIA is a pioneer in accelerated computing, known for inventing the GPU and driving breakthroughs in gaming, computer graphics, high-performance computing, and artificial intelligence. Our technology powers everything from generative AI to autonomous systems, and we continue to shape the future of computing through innovation and collaboration. Within this mission, our team, Managed AI Research Superclusters (MARS), builds and scales the infrastructure, platforms, and tools that enable researchers and engineers to develop the next generation of AI/ML systems. By joining us, you’ll help design solutions that power some of the world’s most advanced computing workloads.
We are seeking a Software Engineer to join our MARS team at NVIDIA. In this role, you will help design, build, and operate exascale infrastructure that powers AI research and development at unprecedented scale. You will work on distributed systems, large-scale storage and compute orchestration, and end-to-end automation that enable AI researchers to focus on innovation rather than infrastructure. You will collaborate closely with engineers and researchers across NVIDIA to architect reliable, efficient, and secure systems that underpin our Managed AI Research Superclusters — infrastructure capable of training frontier models and executing global-scale workloads.
What You’ll Be Doing:
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Design, develop, and operate distributed systems that manage data, compute, and networking for large-scale AI workloads.
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Build software and automation to orchestrate workloads across thousands of GPUs and petabytes of storage in multi-region clusters.
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Collaborate with AI/ML research teams to understand their requirements and translate them into scalable, high-performance solutions.
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Drive improvements in system reliability, performance, and observability to meet exascale standards.
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Partner with security, networking, and platform teams to ensure that MARS infrastructure meets the highest standards of robustness and compliance.
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Participate in design reviews, contribute to system architecture discussions, and influence the evolution of NVIDIA’s AI infrastructure stack.
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Stay current with advances in distributed systems, large-scale computing, and AI frameworks to help shape the future direction of MARS.
What We Need to See:
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BS or equivalent experience in Computer Science, Computer Engineering, or a related technical field.
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5+ years of experience developing and operating large-scale distributed systems, infrastructure platforms, or HPC environments.
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Strong programming skills in C++, Python, or Go, with proven experience designing production-quality software systems.
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Solid understanding of distributed systems principles, data management, and large-scale orchestration frameworks.
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Hands-on experience with high-performance storage (e.g., Lustre, GPFS, BeeGFS) and compute scheduling and orchestration (e.g., Slurm, Kubernetes, LSF).
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Familiarity with cloud environments (Azure, AWS, GCP) and infrastructure automation tools.
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Strong problem-solving skills, ownership mindset, and the ability to thrive in a fast-paced, collaborative environment.
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Excellent communication skills and a track record of cross-functional collaboration.
Ways to Stand Out from the Crowd:
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Graduate degree (MS/PhD or equivalent experience) in Computer Science, Distributed Systems, or a related field.
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Expertise in large-scale data management, cluster scheduling, or workload orchestration at exascale scale.
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Experience building or maintaining infrastructure for AI/ML research, including distributed training pipelines using Py Torch, JAX, or Ne Mo.
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Familiarity with data security, compliance, and lifecycle management for research-scale datasets.
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Demonstrated leadership in system architecture design, performance optimization, or reliability engineering.
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 February 24, 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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3
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0
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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
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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.
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·
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