招聘
必备技能
Docker
Linux
As a member of the Hardware Infrastructure EDA Compute team, you will optimize, scale, and support workload scheduling systems that directly impact design velocity and infrastructure efficiency. Success in this role requires both operational precision along with developing and supporting forward-looking resource management solutions that address evolving compute demands. Beyond day-to-day operations, the role drives improvements in observability, service reliability, and automation, ensuring the EDA compute environment remains resilient, measurable, and aligned with long-term engineering demands.
What you'll be doing:
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Manage, scale, and optimize job scheduling systems (LSF, Slurm, etc.) in a large-scale, multi-site environment supporting EDA and other compute-intensive workloads
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Analyze scheduler and infrastructure performance data to identify systemic bottlenecks and drive measurable improvements in utilization, throughput, and turnaround time
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Lead problem solving across scheduler, OS, and workload layers, ensuring timely resolution of service-impacting issues
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Identify recurring operational challenges and implement targeted automation or process improvements to reduce manual effort and prevent repeat incidents
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Help define and track reliable metrics and SLOs for service performance and reliability, partnering with customers to ensure expectations are realistic and measurable
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Contribute to operational standards, documentation, and best practices to improve consistency across sites
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Partner directly with customer teams to clarify requirements, translate technical tradeoffs, and drive issues to closure
What we need to see:
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Bachelor’s degree in Computer Science or related field, or equivalent experience
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Minimum 5+ years of experience operating and supporting large-scale Linux-based compute infrastructure
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Strong hands-on experience supporting and tuning job scheduling systems (LSF, Slurm, etc.) in HPC or silicon design environments
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Proficiency in Linux systems administration (CentOS/RHEL)
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Strong problem solving skills and the ability to independently analyze complex system behavior under load
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Clear and effective communication skills, including the ability to articulate technical tradeoffs and reliability metrics to engineering stakeholders
Ways to stand out from the crowd:
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Experience implementing reliability engineering practices within HPC scheduling environments
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Deep knowledge of job scheduling systems (LSF, Slurm, etc.) configuration tuning, scheduler internals, and advanced troubleshooting techniques
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Experience building or enhancing observability systems, including metrics collection, monitoring pipelines, alerting strategies, and performance dashboards
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Background with container technologies such as Docker, Singularity, or Podman in HPC environments
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Experience influencing adoption of new infrastructure standards across multiple teams or sites
NVIDIA offers highly competitive salaries and a comprehensive benefits package. We have some of the most forward-thinking and hardworking people in the world on our team and our collaborative talent continues to drive NVIDIA's growth. We are seeking creative and independent engineers with real passion for technology!
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 March 15, 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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关于NVIDIA

NVIDIA
PublicA computing platform company operating at the intersection of graphics, HPC, and AI.
10,001+
员工数
Santa Clara
总部位置
$4.57T
企业估值
评价
4.1
10条评价
工作生活平衡
3.5
薪酬
4.2
企业文化
4.3
职业发展
4.5
管理层
4.0
75%
推荐给朋友
优点
Great culture and supportive environment
Smart colleagues and excellent people
Cutting-edge technology and learning opportunities
缺点
Team-dependent experience and outcomes
Work-life balance issues with long hours
Politics and influence over competence
薪资范围
73个数据点
Junior/L3
Mid/L4
Junior/L3 · Analyst
7份报告
$170,275
年薪总额
基本工资
$130,981
股票
-
奖金
-
$155,480
$234,166
面试经验
7次面试
难度
3.1
/ 5
体验
正面 0%
中性 86%
负面 14%
面试流程
1
Application Review
2
Recruiter Screen
3
Online Assessment
4
Technical Interview
5
System Design Interview
6
Team Review
常见问题
Coding/Algorithm
System Design
Technical Knowledge
Behavioral/STAR
新闻动态
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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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.
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