Teams at NVIDIA

Research and develop GPU-acceleration techniques for high-performance databases, ETL, and data analytics applications. Analyze data-intensive workloads, optimize algorithms, memory management, and CUDA kernels, and investigate CPU/GPU bottlenecks. Collaborate with research, hardware, software, and industry teams to influence next-generation architectures, programming models, and data-processing solutions.

Design, develop, test, and extend NVIDIA’s large-scale object storage platform. Responsibilities include improving availability, reliability, durability, fault tolerance, and performance across deployments exceeding 10,000 nodes and exabytes of data. The role also automates storage infrastructure provisioning, management, and monitoring; supports AI/ML research teams; owns product delivery through support; and contributes to open-source storage projects.

Build and maintain network automation and orchestration software for NVIDIA GPU Cloud and SuperPod deployments. Design/configure centralized configuration management, integrate cloud provider APIs, implement data pipelines and streaming telemetry, and automate lifecycle operations from procurement to deployment. Collaborate with infrastructure experts to deliver zero-touch, production-grade network provisioning, monitoring, and management tools.