As a Solutions Architect, you will engage with partners to drive AI initiatives, support GPU and networking solutions, and manage technical projects in datacenter deployments.

The Senior Deep Learning Engineer will optimize and deploy models for high-performance inference on GPU platforms, aiming to enhance production systems and analyze workload bottlenecks.

Develop cutting-edge techniques in machine learning and deep learning, optimize performance for GPUs, and collaborate on architectural designs.

The Principal Software Architect will lead architecture and design efforts for GPU Networking in AI workloads, focusing on technological innovation in AI data centers, performance optimization, and strategic partnerships.

The role involves guiding partners on NCCL, performing analysis of applications, developing automation tools, and conducting training for HPC applications.

Develop silicon photonics and semiconductor test programs, conduct device characterization, and lead testing concept development. Collaborate for efficient solutions.

Design and develop CUDA-X libraries for NVIDIA CPUs and GPUs, work with partners to understand and deliver on use cases, and lead design reviews.

Develop and optimize math libraries, design user-friendly APIs, collaborate with partners, and research trends in high-performance computing.

The Network Site Reliability Engineer enhances network operations, focusing on automation, monitoring, and user satisfaction while mentoring teams and driving continuous improvement.