
Pioneering accelerated computing and AI
Senior Deep Learning Solution Architect
NVIDIA is leading company of AI computing. At NVIDIA, our employees are passionate about AI, HPC , VISUAL, GAMING. Our SA team is more focusing to bring NVIDIA new technology into difference industries. We help to design the architecture of AI computing platform, analysis the AI and HPC applications to deliver our value to customers, focusing on defining and solving computational challenges in LLM inference and training acceleration, as well as network communication and data transfer optimization.
What You'll Be Doing:
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Contribute to the development of open-source inference frameworks such as SGLang and vLLM, including feature and operator development, performance optimization, and model support, in collaboration with the community.
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Develop and optimize KV cache offloading frameworks for LLM workloads, supporting multi-level cache offloading and reuse across CPU, SSD, and remote storage to improve inference efficiency. (Team project: FlexKV)
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Drive R&D on compute performance in distributed training, and explore methods and technologies for performance optimization.
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Study computational challenges in machine learning systems, identify common needs and bottlenecks, and build example code, acceleration libraries, or frameworks accordingly.
What We Need to See:
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Over 5 years working experience in the technology industry, with master’s degree or above in computer science, mathematics, electrical engineering, automation, or related fields.
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Strong interest in accelerated computing, parallel computing, and heterogeneous computing, with the motivation to explore these areas in depth.
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Solid programming skills, with a good understanding of data structures and computer systems fundamentals.
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Strong learning agility, adaptability, and the ability to analyze, define, and independently explore technical problems.
Ways to Stand Out from the Crowd:
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Familiarity with heterogeneous computing, distributed training, parallel computing, or other areas related to high-performance computing.
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Experience in performance analysis, performance modeling, or performance optimization; contributions to open-source frameworks are a plus.
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Strong ability to define new problems and explore solutions; candidates with independent PhD-level research experience are preferred.
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Proficiency with AI coding tools.
With competitive salaries and a generous benefits package, we are widely considered to be one of the world’s most desirable employers! We have some of the most forward-thinking and hardworking people in the world working for us and, due to outstanding growth, our best-in-class engineering teams are rapidly growing. If you're a creative and autonomous person with a real passion for technology, we want to hear from you.
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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
10条评价
4.4
10条评价
工作生活平衡
2.8
薪酬
4.5
企业文化
4.2
职业发展
4.3
管理层
3.8
78%
推荐率
优点
Cutting-edge technology and innovation
Excellent compensation and benefits
Great team culture and collaboration
缺点
High pressure and expectations
Poor work-life balance and long hours
Fast-paced environment leading to burnout
薪资范围
79个数据点
L3
L4
L5
L3 · Data Scientist IC2
0份报告
$177,542
年薪总额
基本工资
-
股票
-
奖金
-
$150,910
$204,174
面试评价
5条评价
难度
3.0
/ 5
面试流程
1
Application Review
2
Recruiter Screen
3
Technical Phone Screen
4
Onsite/Virtual Interviews
5
Team Matching
6
Offer
常见问题
Coding/Algorithm
System Design
Behavioral/STAR
Technical Knowledge
Past Experience
最新动态
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.
reddit/blind
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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.
reddit/blind
·
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.
reddit/blind
·
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.
reddit/blind
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