招聘
必备技能
Kubernetes
We’re forming a team of innovators to roll out and enhance AI inference solutions at scale, demonstrating NVIDIA’s GPU technology and Kubernetes. As a Solutions Architect focused on inference, you’ll collaborate closely with our engineering, DevOps, and customers to develop enterprise AI solutions. Together, we'll deliver generative AI to production!
What you'll be doing:
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Build inference pipelines with tools like NVIDIA Dynamo, distributing tasks among GPU workers to improve efficiency.
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Collaborate with DevOps teams to orchestrate disaggregated inference using Kubernetes for complex workloads.
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Accelerate inference pipelines using TensorRT-LLM, vLLM, SGLang, and other backends to ensure seamless integration with disaggregated inference.
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Provide mentorship and technical leadership to customers and internal teams, guiding them through the deployment of disaggregated inference systems and resolving complex issues.
What we need to see:
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5+ Years in Solutions Architecture with a proven track record of deploying distributed systems and AI inference workloads on Kubernetes.
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Experience with one of NVIDIA Dynamo, Triton Inference Server, or TensorRT-LLM for model optimization and serving.
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GPU orchestration using NVIDIA GPU Operator, NIM Operator, and Multi-Instance GPU (MIG) partitioning.
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Solving sophisticated GPU allocation, memory hierarchies (HBM, DRAM, SSD), and low-latency networking (RDMA, UCX).
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Demonstrated success in tuning large language models for low-latency inference in enterprise environments.
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BS in CS/Engineering or equivalent experience.
Ways to stand out from the crowd:
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Prior experience deploying NVIDIA inference technologies such as Dynamo, NIM, NIXL and Grove.
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Deep understanding of transformer neural network, and inference acceleration technologies like quantization, speculative decoding, WideEP etc.
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NVIDIA Certified AI Engineer or similar credentials.
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Contributions to open-source projects including NVIDIA Dynamo, vLLM, KServe, or SGLang.
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.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until March 3, 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
4.4
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%
推荐给朋友
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
Junior/L3
Mid/L4
Senior/L5
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
5次面试
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
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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