Senior Architect - Data Processing Systems, Analytics and Data Intelligence
现在,我们正在利用人工智能来定义下一个计算机时代的无限潜力。我们的 GPU 作为能够理解世界的大脑,机器人和自动驾驶汽车的时代。做以前从未完成过的事情需要视觉,创新和世界上最好的才华。作为 NVIDIAN,你将沉浸在多元化的支持环境中,每个人都会受到启发去做自己的最佳工作。加入团队看看你如何对世界产生持久影响。作为分析和数据智能数据处理系统 (ADI) 的高级建筑师,你将定义并改进各种数据处理工作负载的硬件和软件架构。加入我们在使用我们的加速数据处理平台结合 CPU,GPU,高带宽网络等规模上提供卓越性能的使命中!你将做的是:·共同设计 NVIDIA 的数据处理平台未来的架构,目标是性能,效率和成本。· 深入与最终用户,开源社区,ISV,存储合作伙伴和 CSP 进行深入接触,通过将客户见解纳入路线图和参考架构来改善他们的体验。·从 CUDA 内核和加速库到系统级 IO,混动,压缩和数据流动的全堆性能优化驱动。· 与 CPU,GPU 和平台建筑师协作,利用硬件软件共同设计的工作负载分析塑造硬件功能。·与内部团队合作建立并应用基于约束框架和优化解决方案,以实现复杂的设计交易在竞争衡量度中。· 开发比较框架来评估性能敏感性,指导硬件软件合作优化 ·分析整个数据处理环境中的生产工作负载,以确定计算动机,IO 模式和整体平台堆的优化机会。我们需要看到的是:·计算机科学,计算机工程,电气工程或相关领域的 MS 或博士学位,或者相等专业经验。· 8年以上分布式数据平台,数据库,系统工程,性能架构,加速。
查看英文原文
NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.
Are you ready to build the future of data processing with NVIDIA? As a Senior Architect in Data Processing Systems for Analytics and Data Intelligence (ADI), you'll define and improve hardware and software architectures for diverse set of data processing workloads. Join us in our mission to deliver outstanding performance at scale, using our accelerated data processing platform that combines CPUs, GPUs, high-bandwidth networking, and more!
What you'll be doing:
- Co-design future architectures for NVIDIA's data processing platforms, targeting performance, efficiency, and cost.
- Engage deeply with end users, open-source communities, ISVs, storage partners, and CSPs to improve their experience by incorporating customer insights into roadmaps and reference architectures.
- Drive full-stack performance optimization, from CUDA kernels and accelerated libraries to system-level IO, shuffle, compression, and data movement.
- Collaborate with CPU, GPU, and platform architects to shape hardware features using workload analysis for hardware-software co-design.
- Partner with internal teams to build and apply constraint-based frameworks and optimization solvers to navigate complex design trade-offs across competing metrics.
- Develop benchmarking frameworks to evaluate performance sensitivities and guide hardware-software co-optimization
- Analyze production workloads throughout the data processing landscape to identify compute motifs, IO patterns, and optimization opportunities across the full platform stack.
What we need to see:
- MS or PhD in Computer Science, Computer Engineering, Electrical Engineering, or a related field, or equivalent experience.
- 8+ years of experience in distributed data platforms, databases, systems engineering, performance architecture, accelerated computing, or HW/SW co-design.
- Extensive knowledge in one or more of these areas: data processing systems (databases, query engines, or vector search), accelerated computing, high-performance IO, CPU/GPU architecture, or large-scale performance analysis.
- Experience evaluating system-level trade-offs: compute, IO provisioning, memory subsystem development, network topology, and storage tiering across diverse workloads a strong plus.
- Ability to translate sophisticated system analysis into clear, actionable recommendations for silicon architects, software engineers, and executive leadership.
- Ability to work across matrixed organizations to drive alignment and deliver results.
Ways to stand out from the crowd:
- Hands-on experience with GPU-accelerated data processing (cuDF, RAPIDS, cuVS, CUDA).
- Deep familiarity with structured data engines and/or vector database systems.
- Experience with mathematical optimization solvers and understanding of optimization fundamentals.
- Background in network/storage architecture.
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 for Level 4, and 224,000 USD - 356,500 USD for Level 5.You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until October 20, 2026.This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive 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.Originally posted on Himalayas