Jobs at NVIDIA

The Senior HPC Architect role involves deploying large-scale GPU compute clusters, optimizing system administration, and collaborating with researchers on HPC and AI solutions.

The Global Channel GTM Lead will develop strategic channel collaborations, influence partner investments, create enablement systems, and drive sales growth in the AI domain.

The role involves designing, developing, testing, and optimizing software for NVIDIA's SoCs, focusing on performance enhancements and addressing architectural bottlenecks. Responsibilities include competitive analysis and driving performance optimizations across software products.

The role involves deploying AI networking solutions in data centers, driving architectural decisions, troubleshooting network issues, and collaborating on customer projects for NVIDIA's technology solutions.

Lead research and architectural direction for AI systems communication at scale, conducting original research, optimizing hardware-software performance, and mentoring engineers.

Lead the design and implementation of GPU compute clusters for deep learning and high-performance workloads, manage large-scale systems and ensure efficient resource utilization.

The Senior Production Engineer will scale AI infrastructure, manage production systems, implement monitoring capabilities, and ensure reliability and performance across NVIDIA's AI clusters.

The Senior System Software Architect will design, validate, and create enterprise AI factory architectures, collaborating with various teams to optimize deployment strategies and systems performance across compute, storage, and networking infrastructures.

Design and develop scalable infrastructure for deep learning libraries, automate build/test processes, and contribute to open-source tools.

The Senior Formal Verification Engineer will verify sophisticated ASIC builds using formal methods, collaborate with architecture teams, develop verification environments, and support silicon debug.

Profile, benchmark, and optimize large-scale LLM training and inference across GPUs, CPUs, HCAs, and switches. Focus on collective communication and high-performance networking, build PyTorch trace-based profiling and replay tools, define performance test plans, and collaborate across hardware and software teams to identify bottlenecks and achieve performance targets.

The role involves performing data analysis for datacenter applications, using machine learning for GPU systems, and providing insights on trends to enhance workflows.

Lead cross-disciplinary software architecture for next-generation CPUs and SoCs, collaborating with hardware, software, ASIC, verification, and platform teams. Influence hardware decisions via deep system software, OS/driver, and performance expertise, advise partners and senior management, and drive optimized solutions for AI and HPC workloads.

The role involves developing backend infrastructure features, ensuring high performance, debugging, collaborating cross-functionally, and optimizing code for cloud-based simulations.

Lead demand creation, co-selling, forecasting, and relationship management with USAF and USSF customers to grow NVIDIA Data Center, Edge, and Cloud product adoption. Act as primary account owner, build strategic partnerships, collaborate with OEMs and integrators, and communicate technical value to senior leaders. Travel to customer sites and events as required.

Design, deploy, and operate Kubernetes-based large-scale storage and data platforms. Build automation, tooling, telemetry, and observability. Troubleshoot distributed systems, support CI/CD and IaC, participate in on-call rotations, capacity planning, and launch readiness.

Architect, build, and scale high-performance ML platform infrastructure using IaC (Ansible, Terraform). Apply SRE practices to ensure reliability across multi-cloud and on-prem GPU clusters, develop automation and orchestration tooling, operate Kubernetes/Docker workloads, participate in on-call rotation, and collaborate with researchers to support end-to-end ML workflows.

The Senior Software Engineer will develop and integrate AI systems, focusing on improvement and evaluation. Responsibilities include designing APIs and monitoring tools, optimizing performance, and collaborating with cross-functional teams.

Develop AI systems for efficient inference, design and optimize kernels, and build domain-specific compilers and runtimes while collaborating with engineers.

Lead the design and operation of large scale Kubernetes clusters, ensuring high availability and performance while supporting system lifecycle and reliability improvements.