Lead the architecture, deployment, and day-to-day technical ownership of a hybrid GPU supercomputing environment integrated with physical quantum processors. Responsibilities include Linux/HPC system administration, job scheduler (Slurm) operations, networking, storage, containerized workloads, quantum control integration, application enablement, and collaboration with quantum hardware vendors. Requires 12+ years operating production HPC or large-scale compute infrastructure and familiarity with quantum hardware and software toolchains.

NVIDIA seeks a hands-on Senior Solutions Architect to solve Day 2 operational problems for NVIDIA Cloud Partners, making validated solutions reusable across the ecosystem. The role requires extensive experience building and operating distributed, GPU/HPC or cloud infrastructure (deep expertise in areas such as Kubernetes/Slurm, observability, storage, networking, and automation) and strong skills in troubleshooting, collaboration, and communication. Base salary range listed: 224,000 USD - 356,500 USD per year.

Role involves designing and executing performance studies, establishing baselines, diagnosing regressions, and driving optimizations for large-scale AI workloads. Requires BS or higher in CS/CE or related field, 12+ years of experience, strong C++ and Python skills, and solid foundation in operating systems, computer architecture, distributed systems, benchmarking, profiling, and optimization. Experience with CUDA, GPU systems, and deep learning frameworks is a plus.

Lead technical strategy and execution for core Kubernetes platform capabilities including cluster management, control plane services, fleet lifecycle, and day-2 operations. Build reliable distributed systems and APIs for provisioning, upgrading, operating, and remediating Kubernetes clusters at scale across cloud and on-premises environments. Mentor engineers, influence architecture, and drive cross-functional initiatives.

Role involves architecting, deploying, and tuning large-scale HPC and AI clusters (CPU/GPU), managing job scheduling and orchestration (e.g., Slurm, Kubernetes), developing CI/CD pipelines and automation, deploying monitoring/logging/alerting, troubleshooting from bare metal to application level, and supporting R&D and POCs. Requires strong Linux/Windows, networking, storage, scripting, and virtualization knowledge.

Join NVIDIA’s DGX Cloud DSX Kubernetes Fleet team to design and implement software that manages a fleet of GPU/DPU-accelerated Kubernetes clusters. Responsibilities include building APIs and workflows, automation of build/test/release, provisioning, upgrades, and lifecycle management. Requires 10+ years experience, expert-level systems programming in Go/C, strong Kubernetes and container technology knowledge, deep Linux/kernel internals experience, cloud and distributed systems background, and hands-on CI/CD and automation experience.

Lead design and development of software to manage a fleet of GPU- and DPU-accelerated Kubernetes clusters, including automation of provisioning, upgrades, deployment pipelines, and lifecycle management. Requires deep experience with Kubernetes, systems programming (Go, C), Linux kernel internals, CI/CD automation, cloud and distributed systems, and production reliability and security.

NVIDIA is hiring a Senior Deep Learning Software Infrastructure Engineer to craft, scale, and harden training libraries and infrastructure for large-scale autonomous driving model training. The role requires designing orchestration and distributed training systems, optimizing data loaders and performance, and collaborating with researchers and platform teams. Candidates should have 12+ years building high-performance distributed systems and strong experience with PyTorch, large-scale training (DDP/FSDP), NCCL, datacenter networking, parallel filesystems, schedulers (Slurm/Kubernetes), and Python.

NVIDIA is hiring a Senior AI/ML HPC Cluster Engineer to lead day-to-day operations, reliability, and performance optimization of on-premises and cloud GPU clusters. The role requires a minimum of 5 years' experience with large-scale compute infrastructure and hands-on skills with schedulers (e.g., Slurm, K8s, PBS), Linux administration, configuration management, container technologies, Python/bash scripting, and MPI-based workflows.

Join NVIDIA's Cloud Foundations Automation team to architect, develop, and operate secure, scalable cloud-native platform services and infrastructure automation for DGX Cloud and SuperPod. Requires 8+ years' experience and strong proficiency in Python and Go, Kubernetes, infrastructure automation (Terraform, Ansible), workflow orchestration (Temporal), distributed systems (databases, Redis, Kafka/NATS/SQS), observability (Prometheus/Grafana/OpenTelemetry), networking, and Linux. Salary ranges provided in the posting.

Join NVIDIA's Performance and R&D teams to profile and benchmark AI and HPC workloads on GPU and CPU clusters, analyze networking and system-level performance (RDMA, MPI, NCCL, RoCE), develop diagnostic and benchmarking tools, and collaborate with hardware, firmware, networking, and software teams to produce reproducible performance insights.

Join NVIDIA's Infrastructure Specialists team to set up, tune, and validate AI factory environments across multi-GPU/multi-node Linux clusters. Responsibilities include running and analyzing AI/LLM benchmarks, diagnosing failures/hangs/low performance, applying observability and automation (Python/Shell) for benchmarking and regression checks, and collaborating with hardware/software/network/product teams. Requires 5+ years managing Linux systems in HPC/distributed/AI environments and hands-on experience with multi-GPU or multi-node AI/ML workloads and NCCL/collective communication patterns.

NVIDIA seeks a Senior Solutions Architect with 6+ years in AI infrastructure, HPC, networking, or SRE to design, profile, and optimize large-scale GPU clusters (on-prem and cloud). Responsibilities include troubleshooting GPU networks (InfiniBand, RoCE, RDMA), debugging NCCL, leading POCs, and partnering with engineering and sales. Remote work is supported; occasional travel (~20%) required.

Lead and coach a team of Storage Production Engineers to design, deploy, and improve distributed, parallel file, and object storage systems. Own capacity planning, lifecycle management, high availability, disaster recovery, incident response, and operational KPIs. Requires hands-on experience with enterprise storage platforms, storage networking/protocols, automation/IaC, and monitoring/observability. 12+ years experience and 6+ years of people/technical leadership are required.

NVIDIA is hiring a Senior Software Engineer (Resilience Engineering) for DGX Cloud to lead org-wide reliability strategy, establish and maintain SLOs, lead high-severity incident response, implement chaos engineering and failure-injection practices, and improve production code and tooling. The role asks for 8+ years of industry experience, deep experience running large-scale production systems, practical reliability experience, and proficiency in Go, Python, or similar languages. Listed salary range: USD 184,000–356,500 (base, annual across levels).

NVIDIA seeks a Senior Performance Engineer to design and execute performance studies, establish baselines, diagnose bottlenecks, and drive optimizations for DGX Cloud AI workloads. The role requires strong programming in C++ and Python, deep knowledge of operating systems, computer architecture, distributed systems, and experience with performance engineering, profiling, and benchmarking; experience with CUDA, GPU performance analysis, and deep learning frameworks (PyTorch, JAX/XLA) is listed as a differentiator.

Role focused on designing, implementing, and maintaining an agent harness and the systems to run and reproduce experiments for AI safety and security. Requires 5+ years software engineering experience, strong Python skills, familiarity with containerized environments and CI/CD, and experience with agent frameworks/ML infrastructure (NeMo experience is a plus). Base salary range: 152,000 USD - 241,500 USD.

Role coordinates and communicates operational incident response and maintenance across NVIDIA’s datacenter portfolio, develops reliability programs and health scoring, drives automation and process improvements, performs failure analysis and root cause investigations, and manages disaster recovery and audit activities. Requires 5+ years of datacenter operations or EHS experience and proficiency with DCIM/asset databases, statistical analysis, and reporting.

NVIDIA seeks a Senior NCX Engineer to work with strategic customers and partners to build, deploy, and optimize AI workloads (training and inference) on NCP, Neo Cloud, DGX Cloud and major CSPs. The role requires customer-facing experience, expertise in Kubernetes, containers, GPU scheduling, Linux, Python/Go, ML frameworks (PyTorch/TensorFlow), observability and infrastructure-as-code practices.

Lead technical architect for NVIDIA's client platform services focused on building scalable tooling and automated service delivery across global endpoint fleets. Role requires 12+ years in client platform engineering, mastery of IaC/CaC (e.g., Terraform, Ansible, Chef, Puppet), Git-based CI/CD, proficiency in Python/Go/Rust, and experience building internal tooling, CLI tools, or microservices to automate platform operations. Responsibilities include setting technical standards, mentoring engineers, collaborating with Security/Networking/Product teams, and driving reliability and developer productivity improvements.