NVIDIA
Senior Architect - Data Processing Systems, Analytics and Data Intelligence
Be an Early Applicant
Define and improve hardware and software architectures for NVIDIA data processing platforms. The role focuses on hardware-software co-design, full-stack performance optimization, benchmarking, workload analysis, system trade-offs, and collaboration with customers, partners, architects, and engineering teams to guide scalable accelerated computing solutions.
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.Similar Jobs
Artificial Intelligence • Fintech • Insurance • Marketing Tech • Software • Analytics
Handle inbound calls and warm leads, consult customers on insurance needs, recommend appropriate Property and Casualty products and coverages, and convert prospects into policyholders. Represent the Liberty Mutual brand while delivering customer-focused service and meeting sales goals. Complete paid training and licensing requirements, work a specified weekday and weekend schedule, and maintain a compliant remote workspace with reliable wired high-speed internet.
Top Skills:
Cable InternetDslFiber InternetPcWired High-Speed Internet
2 Hours Ago
Automotive • Big Data • Information Technology • Robotics • Software • Transportation • Manufacturing
Analyzes autonomous-vehicle telemetry, time-series signals, incidents, software releases, and operational data to investigate safety issues and root causes. Integrates diverse data sources into analysis-ready datasets, validates data quality, applies engineering and signal-processing methods, and delivers rigorous findings for safety assurance and operational decisions. The role also develops reusable detection methods, metrics, pipelines, and analytical tooling while collaborating across engineering, operations, safety, human factors, and data teams.
Top Skills:
BigQueryC++Ci/CdCloud Data PlatformsDistributed ProcessingDockerGitKubernetesPythonRobot Operating System (Ros)Signal ProcessingSQLTime-Series Analysis
Automotive • Big Data • Information Technology • Robotics • Software • Transportation • Manufacturing
Leads GM Europe's commercial performance across the UK and Ireland, translating regional strategy into country plans and driving sales, service, revenue, profitability, customer experience, and network effectiveness. Manages dealerships, fleet customers, distributors, and other route-to-market partners; coordinates marketing, product, distribution, inventory, and service activities; leads cross-functional initiatives; and develops a high-performing country organization while ensuring compliance, governance, and risk management.
What you need to know about the Colorado Tech Scene
With a business-friendly climate and research universities like CU Boulder and Colorado State, Colorado has made a name for itself as a startup ecosystem. The state boasts a skilled workforce and high quality of life thanks to its affordable housing, vibrant cultural scene and unparalleled opportunities for outdoor recreation. Colorado is also home to the National Renewable Energy Laboratory, helping cement its status as a hub for renewable energy innovation.
Key Facts About Colorado Tech
- Number of Tech Workers: 260,000; 8.5% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Lockheed Martin, Century Link, Comcast, BAE Systems, Level 3
- Key Industries: Software, artificial intelligence, aerospace, e-commerce, fintech, healthtech
- Funding Landscape: $4.9 billion in VC funding in 2024 (Pitchbook)
- Notable Investors: Access Venture Partners, Ridgeline Ventures, Techstars, Blackhorn Ventures
- Research Centers and Universities: Colorado School of Mines, University of Colorado Boulder, University of Denver, Colorado State University, Mesa Laboratory, Space Science Institute, National Center for Atmospheric Research, National Renewable Energy Laboratory, Gottlieb Institute
