招聘
必备技能
PyTorch
Help build an Always-On, low-overhead GPU profiling service that runs in production, scales across cluster environments, and delivers actionable insights for ML workloads. You will be hands-on delivering our profiling solutions across system software, drivers, and CUDA to make profiling continuously available and reliable.
What you’ll be doing:
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Develop low-overhead, high-reliability implementations in C/C++, with bounded CPU/memory budgets.
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Lead end-to-end feature delivery spanning user-mode components, driver/platform layers, and performance counter/trace providers.
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Establish profiling models that integrate with existing ML/AI workflows (e.g., Py Torch/XLA) to turn low-level signals into actionable insights.
What we need to see:
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BS or MS degree or equivalent experience in Computer Engineering, Computer Science, or related degree.
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5+ years of system-level C/C++ development, including concurrency, memory management, and performance engineering.
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Familiarity with system software design, operating systems fundamentals, computer architectures, performance analysis, and delivering production-quality software.
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Strong interpersonal, verbal, and written communication; able to influence across organizations and build trust with external collaborators.
Ways to stand out from the crowd:
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Extensive experience with profiling/tracing stacks for CPU/GPU (e.g., CUPTI, Nsight, performance counters, event correlation) and debugging highly concurrent systems.
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Deep hands-on knowledge of CUDA and GPU architecture, including runtime/driver APIs, CUDA streams/graphs, and kernel behavior.
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Track record building continuous, always-on, or multi-client profiling systems designed for predictable overhead at scale.
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Hands-on experience tuning ML training/inference loops based on deep profiling analysis, with familiarity in ML ecosystems (e.g., Py Torch, JAX) and correlating application events with GPU metrics to translate data into actionable performance insights (e.g., bottleneck triage, compute vs. memory bound).
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Experience with user-mode driver development and integration within platform security and permissions models.
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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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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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