Solutions Engineer

• Assist in supporting industry accounts and driving research/influencing/new business in those accounts.
• Assist researchers/engineers on their GPU applications.
• Deliver technical projects, demos and client support tasks as directed by the Solution Architecture leadership team.
• Provide technical support for GPU system deployments.
• Be an industry thought leader on integrating NVIDIA technology into applications built on Deep Learning, High Performance Data Analytics, Robotics, Signal Processing and other key applications.
• Be an internal champion for Data Analytics, Machine Learning, and Cyber among the NVIDIA technical community.

Deep Learning Solution Architect

• Work with Sales, BD and CPM team to introduce NVIDIA technologies into assigned accounts and grow business accordingly.
• Lead the design, development, and optimization of Kubernetes-based infrastructure solutions for Agentic AI and Agentic RL workloads, addressing core challenges including massive concurrent sandbox scheduling, millisecond-level elasticity, secure isolation, and full-scenario interactive environment support.
• Collaborate closely with NVIDIA’s CSP partners (major cloud service providers in China) to understand their Agentic AI/RL business needs, provide professional K8s technical guidance, and tailor infrastructure solutions that align with NVIDIA’s accelerated computing technologies (such as NVIDIA AI Enterprise, GB200 platform, and NVCF).
• Optimize Kubernetes clusters to support high-throughput, low-latency Agentic RL training and inference workloads, including resource scheduling strategy optimization, GPU resource management, network and storage performance tuning, and solving bottlenecks in large-scale Pod creation and scheduling.
• Design and implement Agent Infra core components based on K8s, such as secure sandbox environments, interactive trajectory recording, checkpoint breakpoint replay, and full-link observability tools, to support the end-to-end lifecycle of Agentic AI/RL development and deployment.
• Work with cross-functional teams (NVIDIA’s R&D, solution architecture, and technical support teams) to promote the integration of K8s with NVIDIA’s software and hardware ecosystem, including NVIDIA Operators, Dynamo, Grove, and KAI Scheduler, to achieve optimal performance of Agentic workloads.
• Provide technical leadership in K8s and Agentic AI/RL Infra fields, guide junior engineers, and drive the continuous iteration and improvement of infrastructure solutions based on industry best practices and customer feedback.
• Stay abreast of the latest trends in Kubernetes, Agentic AI, Agentic RL, and cloud-native infrastructure, introduce advanced technologies and solutions into NVIDIA’s CSP ecosystem, and promote technological innovation and standardization.
• Participate in technical pre-sales support, solution demonstration, and technical training for CSP partners, helping partners master K8s-based Agentic AI/RL Infra construction and operation capabilities.

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Deep Learning Solution Architect

Senior Solutions Architect, CSP System