What you'll be doing:
- Engage with NVIDIA Cloud Partners (NCP) to drive initiatives, shape new business opportunities, and cultivate collaborations in the field of Artificial Intelligence (AI), contributing to the development of our cloud solutions.
- Serve as a technical specialist for GPU and networking products, collaborating closely with sales account managers to secure design wins and actively engaging with customer engineers, management, and architects at key accounts.
- Conduct regular technical customer meetings to discuss project and product roadmaps, features, and introduce new technology solutions.
- Develop custom product demonstrations and Proof of Concepts (POCs) addressing critical business needs, supporting sales efforts.
- Strong technical presentation skills, confidence in developing Proofs-of-Concept, and a customer-focused mentality, coupled with good organization skills, a logical approach to problem-solving and effective time management for handling concurrent requests.
Candidate should demonstrate knowledge in some of the below areas :
- BS/MS/PhD or equivalent experience in Computer Science, Data Science, Electrical/Computer Engineering, Physics, Mathematics, other Engineering fields with at least 3 years work or research experience in networking fundamentals, TCP/IP stack, and data center architecture.
- Ideal candidate possesses 3 years of Solution Architect or similar Sales Engineering experience, demonstrating motivation and skills to drive the technical pre-sales process.
- Deep expertise in datacenter engineering, GPU, networking, including a solid understanding of network topologies, server and storage architecture.
- Proficiency in system-level aspects, encompassing Operating Systems, Linux kernel drivers, GPUs, NICs, and hardware architecture.
- Demonstrated knowledge in cloud orchestration software and job schedulers, including platforms like Kubernetes, Docker Swarm, Run AI and Slurm
- Familiarity with cloud-native technologies and their integration with traditional infrastructure is essential.
- Knowledge in InfiniBand and Artificial Intelligence infrastructure.
- Demonstrated hands-on experience with NVIDIA systems/SDKs CUDA, NVIDIA Networking technologies DPU, RoCE, InfiniBand, ARM CPU solutions, coupled with proficiency in C/C++ programming, parallel programming, and GPU development.
- Knowledge of DevOps/MLOps technologies such as Docker/containers, Kubernetes, compute/network/storage deployments.
- Large scale systems management experience.
- Experience with Python programming and AI workflow development and deployment (training/inference) would be advantageous