Senior Architect - Data Processing Systems, Analytics and Data Intelligence
This is the employer's own posting, not a copy on a job board.
What we know
Is it still open?
Confirmed still open
Last checked just now — checked against the employer's own applicant tracking system, which is the company answering directly.
We re-read the employer's own applicant tracking system and the posting was still there. That is the company answering directly.
How old is it?
Posted 15h ago
The date the source published, not the day we noticed it (2026-10-16). Last seen at its source 1h ago.
Is it remote?
US, Remote
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Who may apply?
United States
The description states no restriction of its own. This is the source's own tag.
Pay
$184k–287.5k/yr
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Skills named in the ad
Recognised terms only, from a fixed vocabulary — this is what CV matching compares against.
Carried by 1 source
-
Workday employer's own board first seen 1h ago · last seen 1h ago
The listing
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.
You will also be eligible for equity and benefits.
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.