Role in NVIDIA's Analytics and Data Intelligence group to develop and optimize libcudf and related projects (Velox/Presto) for GPU-accelerated DataFrame and database operations. Requires 8+ years of experience, strong modern C++ and CUDA skills, and experience with distributed GPU performance, communication protocols (e.g., UCX/NCCL), and open-source development. Remote positions listed with locations in the United States.

NVIDIA is hiring an AI Compiler Engineer to work on kernel generation, computational graph optimizations, and compiler frameworks for next-generation GPUs. The role requires 3+ years of relevant industry compiler experience, hands-on MLIR knowledge, and strong C/C++ and Python programming and software design abilities. Collaboration with hardware, software, and research teams and experience with AI workloads (inference/training, LLMs, datacenter deployments) are emphasized.

Work on design, development, and operation of multi-tenant cloud SDN control and data plane software (OVS/OVN/OpenFlow) for NVIDIA AI Cloud. Role requires strong programming in C and Go, scripting in Bash/Python, Kubernetes/CNI experience, CI/CD and GitOps experience, and 8+ years in large-scale distributed environments. Location: US (Santa Clara) / Remote. Listed base salary range: 184,000–287,500 USD per year.

Join a team building and improving GPU/CPU-accelerated libraries (nvComp, NPP, nvJPEG, nvJPEG2000, nvTIFF, nvImageCodec). The role involves designing and optimizing algorithms, performance tuning and benchmarking on modern architectures, and collaborating with product and engineering teams.

Work on GPU- and CPU-accelerated libraries used for AI, data analytics, image processing, and scientific simulations. Responsibilities include developing scalable library software, performance tuning and benchmarking, collaborating with product teams, and providing technical leadership. Requires 12+ years of experience in high-performance parallel numerical applications and GPU acceleration (CUDA).

Customer-facing role combining ~50% troubleshooting/customer support and ~50% R&D. Responsibilities include owning Ethernet/InfiniBand/DPU deployments end-to-end, developing features and tools for enterprise networking products, and collaborating with engineering to reproduce and solve complex issues. Requires BSc (or equivalent) and 8+ years of system software development with strong C/C++ and Linux networking expertise.

Lead development of global strategy and architectures for scaled-out, high-throughput low-latency AI inference. Responsibilities include designing distributed pipelines and orchestration layers, hardware-software co-optimization (GPU/CUDA/kernels/drivers), model lifecycle automation (deployment, versioning, scaling), and collaborating with customers and open source ecosystems (TensorRT-LLM, vLLM, Ray, Kubernetes). Requires 16+ years technical experience and deep expertise in GPU acceleration and production distributed systems.

Lead security engineering for RTOS, hypervisor, and embedded virtualization across design, implementation, review, and verification; collaborate on CPU/SoC security, perform threat modeling and automotive TARA, review low-level C/C++ code, build fuzzing and security test infrastructure, and drive fixes to production. Requires 8+ years of relevant experience.

NVIDIA seeks a Principal Software Engineer to lead technical strategy and execution for production-grade Kubernetes lifecycle systems and core platform capabilities (cluster management, control plane services, fleet lifecycle, day-2 operations) across cloud and on-premises. Requires 15+ years of relevant software engineering experience, deep Kubernetes and distributed systems expertise, strong systems programming skills (Go/Python/Rust/C++), and leadership/mentoring experience. Posted salary range: 272,000–431,250 USD per year.

NVIDIA seeks a Software & System Architect to define architectures for DPUs, NICs and cloud networking, including orchestration, provisioning and security. The role requires designing end-to-end solutions (application to hardware), evaluating technologies, building POCs, and collaborating with global SW/HW teams and customers. Minimum qualifications include a degree in a relevant field and 2+ years' experience as a software/system architect and as a software developer, with strong skills in C, Python, Linux and container technologies.

Design, build and optimize GPU-accelerated software and inference pipelines for state-of-the-art LLMs, multimodal and generative AI across NVIDIA accelerators. Contribute to and maintain inference frameworks (vLLM, SGLang, FlashInfer), use tools/plugins such as CUTLASS, Triton, NCCL and CUDA kernels, and work with cross-functional teams to drive performance improvements. Requires MSc/PhD or equivalent experience and 5+ years of relevant software development experience with strong C/C++ skills.

Optimize and benchmark system software for NVIDIA automotive performance platforms (Safe RTOS), collaborate with hardware, DriveOS, power and test teams, and develop profiling tools. Requires a Master’s degree or equivalent, minimum 12 years of systems/software performance experience, strong C/C++ skills, Linux and QNX knowledge; experience with hypervisors, benchmarking and profiling; AI/ML experience desirable.

Responsible for crafting, scaling, and hardening deep learning infrastructure and libraries for multi-thousand GPU training clusters, improving data loaders, distributed training, scheduling, and performance monitoring, and owning orchestration and fault-resilient training systems. Requires 12+ years building high-performance distributed systems, strong Python and PyTorch experience, large-scale training expertise (DDP/FSDP, NCCL, parallelism), and systems knowledge including datacenter networking, Lustre, Slurm/Kubernetes, and storage.

Senior Developer Technology Engineer role focused on researching and implementing GPU-acceleration and memory/algorithm optimizations for high-performance databases and ETL/data-analytics workloads. Requires a masters/PhD (or equivalent), 5+ years' relevant experience, programming fluency in C/C++, low-level parallel programming experience (e.g., CUDA, OpenACC, OpenMP, MPI, pthreads, TBB), and expertise in CPU/GPU architecture and memory subsystems. Location: US (hybrid). Salary ranges provided per location and level.

Lead and scale an engineering team developing and optimizing open-source deep learning inference frameworks (vLLM/SGLang, FlashInfer, etc.) for NVIDIA GPUs. Responsibilities include roadmap and strategy, cross-team collaboration with compilers/libraries/research, performance tuning and profiling for LLMs and multimodal models, and mentoring engineers. Requires 6+ years software development experience and 3+ years technical leadership; strong C/C++ and GPU programming experience (CUDA, Triton, CUTLASS).

Build, operate, and automate cloud-native platform services (Python/Go) on Kubernetes to support DGX Cloud and SuperPod deployments. Responsibilities include infrastructure orchestration, self-service workflows, integrations, observability, security, and collaboration with networking and infrastructure teams. Requires BS or equivalent and 8+ years of relevant experience; experience with Terraform, Ansible, Temporal, databases, messaging (Kafka/NATS/SQS), Prometheus/Grafana/OpenTelemetry, and networking/security technologies.

Develop, test, and optimize system software and firmware for SoCs in O-RAN Radio Units and Distributed Units, including power-management policies (DVFS, clock/power gating, thermal controls), performance measurement, modeling, and workload analysis across CPU/GPU/accelerators and interconnects. Requires a BS/MS or equivalent, 5+ years of relevant experience, strong C/C++ and scripting skills (Python), Linux kernel and device driver experience, and knowledge of cellular interface standards (e.g., 3GPP NR, O-RAN Open Fronthaul, eCPRI).

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.

Experienced software engineer to develop and maintain automation tooling and orchestration for NVIDIA's GPU Cloud and SuperPod deployments. Responsibilities include building network design and configuration management solutions, integrating with cloud provider APIs, working with DCIM tools (NetBox/Nautobot), implementing containerized services (Kubernetes/EKS), and developing streaming/event pipeline architectures. Requires strong background in networking, network automation, Python and Go, and 12+ years of relevant experience.

NVIDIA is hiring a senior system software engineer to design and implement features in the CUDA driver for Microsoft Windows. The role requires strong C/C++ skills, experience with operating system interfaces, multithreaded programming, system architecture, and working on large codebases; Windows driver and kernel-mode experience, GPU/graphics knowledge, and WDDM experience are listed as differentiators. The posting includes salary ranges and is open through November 3, 2026.