招聘
必备技能
Python
PyTorch
TensorFlow
Machine Learning
We're looking for outstanding AI systems engineers to develop groundbreaking technologies in the inference systems software stack! We build innovative AI systems software to accelerate for AI inference. As a member of the team, you'll develop libraries, code generators, and GPU kernel technologies for NVIDIA's hardware architecture. This means designing and building things like new abstractions, efficient attention kernel implementations, new LLM inference runtimes components, and kernel code generators to accelerate large language models, agents, and other high-impact AI workloads.
What you'll be doing:
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Innovating and developing new AI systems technologies for efficient inference
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Designing, implementing, and optimizing kernels for high impact AI workloads
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Designing and implementing extensible abstractions for LLM serving engines
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Building efficient just-in-time domain specific compilers and runtimes
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Collaborating closely with other engineers at NVIDIA across deep learning frameworks, libraries, kernels, and GPU arch teams
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Contributing to open source communities like Flash Infer, vLLM, and SGLang
What we need to see:
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Masters degree in Computer Science, Electrical Engineering, or related field (or equivalent experience); PhD are preferred
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6+ years (academic/ industry) experience with ML/DL systems development preferable
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Strong experience in developing or using deep learning frameworks (e.g. Py Torch, JAX, Tensor Flow, ONNX, etc) and ideally inference engines and runtimes such as vLLM, SGLang, and MLC.
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Strong Python and C/C++ programming skills
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Strong experience in GPU kernel development and performance optimizations (especially using CUDA C/C++, cu Tile, Triton, or similar)
Ways to stand out from the crowd:
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Background in domain specific compiler and library solutions for LLM inference and training (e.g. Flash Infer, Flash Attention)
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Expertise in inference engines like v
LLM and SGLang:
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Expertise in machine learning compilers (e.g. Apache TVM, MLIR)
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Open source project ownership or contributions
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD.
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
47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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