Integration Engineer supporting clients with their integrations to optimize fraud detection systems at Ravelin. Collaborating with internal teams to ensure the best client experience.
About the role
- Senior Solutions Architect driving deployment of AI hardware and software technologies in customer data centers. Collaborating with teams to solve complex engineering challenges and enhance product roadmaps.
Responsibilities
- Working with NVIDIA AI Native and Consumer Internet customers on large data center GPU server and networking system deployments as Solution Architect Engineer.
- Guide customer discussions on network design, compute/storage and support bring up of server/network/cluster deployments.
- You will need to visit customer data center during bring up phase.
- Demonstrate subject matter expertise in advanced GPU & network systems and be a trusted technical advisor to NVIDIA's strategic customers.
- Bring customer-specific requirements to product teams to guide product roadmap features.
- Identify new project opportunities for NVIDIA products and technology solutions in data center and artificial intelligence applications.
- Work closely with the GPU/Network Systems Engineering, Product management and Sales teams.
- Work as customer trusted advisor conducting regular technical customer meetings for product roadmap, cluster issues debug, feature discussions and introduction to new technology solutions.
- Build custom product demonstrations and POCs for solutions that address critical business needs of our customers.
- Analyze and debug compute/network configuration, performance issues to deliver performant clusters.
Requirements
- BS/MS/PhD in Electrical/Computer Engineering, Computer Science, Physics, or other Engineering fields or equivalent experience.
- 8+ years of Systems/Solution Engineering (or similar Engineering roles) experience.
- System level expertise of CPU/GPU server architecture, NICs, Linux, system software and kernel drivers.
- Experience with networking switches for Ethernet/Infiniband, and Data Center infrastructure (power/cooling).
- Knowledge of DevOps/MLOps technologies such as Docker/containers, Kubernetes.
- Effective time management and capable of balancing multiple tasks.
- Strong verbal/written communication skills and share your ideas/code clearly through documents, presentation etc.
Benefits
- equity
- benefits
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