位于c23的 20 个优质data architect职位（正在招聘！）

NVIDIA is looking for an enthusiastic and forward-thinking solution architect to help in the enablement of Industry Software Vendors (ISVs). These ISVs are developing the Agentic AI stack for multiply workloads which will be used to empower industry customers.

As part of the Solution Architecture team, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Join the team and see how you can make a lasting impact on the world by applying AI technology to mass market.

What you'll be doing:

Work with ISVs and end customers to understand their system architecture, technical requirements, and business workflows, then guide them toward the best NVIDIA-based solution.
Architect hybrid and multi-cloud AI solutions, guiding ISVs and customers on deploying GPU-accelerated workloads across major public clouds and private data centers.
Design and optimize scalable AI infrastructure solutions, providing best-practice guidance on configuring CPU/GPU servers, storage, and networking for high-performance workloads.
Support technical discovery, proof-of-concept development, infrastructure validation, and production adoption for industry software platforms.
Provide technical leadership in deploying AI applications across diverse environments, including bare-metal servers, virtualized instances, and cloud-native containerized clusters.
Collaborate with headquarters engineering, product, and partner teams in English to resolve technical issues, influence roadmap alignment, and ensure strong execution for strategic ISV engagements.
Analyze infrastructure bottlenecks, cluster behavior, and deployment trade-offs, then recommend practical architectures that improve performance, scalability, and usability for customers.

What we need to see:

MSc/PhD in Computer Science, Electrical Engineering, IT Infrastructure, or related field (or equivalent experience).
3+ years in infrastructure/cloud architecture, technical consulting, or customer-facing technical roles.
Strong domain expertise with understanding of enterprise infrastructure and real-world workflows.
Knowledge of GPU architecture and its application in accelerating modern workloads.
Hands-on experience with enterprise IT infrastructure, including CPU/GPU servers, data centers, and HPC environments.
Experience with major cloud platforms, especially GPU-accelerated instances and AI services.
Proficiency in cloud-native tech, containerization (Docker/Podman), and orchestration tools (Kubernetes/Slurm).
Strong communication skills to translate technical concepts for business stakeholders and collaborate across global teams.

Ways to stand out from the crowd:

Experience working with Independent Software Vendors (ISVs), enterprise software platforms, or technical partner ecosystems.
Deep expertise in AI infrastructure (AI infra) architecture, including large-scale CPU/GPU cluster design, AI job scheduling, and performance tuning for LLM training/inference.
Relevant cloud architecture certifications or deep expertise in building edge-to-cloud scalable AI infrastructures.
Strong customer engagement skills with a proven record of helping partners and customers succeed through technical leadership and execution.

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