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 compiler optimization algorithms for deep learning workloads targeting NVIDIA GPUs, optimizing JAX and OpenXLA performance for training and inference. Responsibilities include graph optimization, tensor sharding and partitioning for distributed workloads, performance tuning, and code generation using open-source compilers (MLIR, LLVM, Triton). Requires a BS/MS/PhD or equivalent experience, 4+ years of relevant experience, strong C/C++ skills, and familiarity with GPU architectures and high-performance/distributed programming.

NVIDIA seeks a Senior Deep Learning Algorithm Engineer to expand Megatron Core and NeMo Framework capabilities for LLM and multimodal workloads. Responsibilities include designing distributed training algorithms, model parallelism, performance tuning on NVIDIA GPUs, contributing to open-source frameworks, and collaborating with internal and open-source partners. Requires MS/PhD or equivalent, 5+ years industry experience, strong DL fundamentals, and proficiency in Python and frameworks such as PyTorch, JAX, or Ray.

Role focused on architecting and building agentic systems (coding and research domains), analyzing inference workload dynamics of agent harnesses under realistic conditions, and collaborating with evaluation teams for software and hardware. Requires strong experience building AI agents and evaluating agent performance; MS in Computer Science (or equivalent) with 5 years of software development experience. Listed base salary ranges: $152,000–$241,500 (Level 3) and $184,000–$287,500 (Level 4).

Role focuses on full lifecycle development and operation of multi-tenant cloud SDN control and data plane software (OVS, OVN, OpenFlow), network orchestration (gRPC/REST), observability, CI/CD (GitLab), and production reliability. Requires 8+ years' experience, expert knowledge of OVN/OVS/OpenFlow, strong C and Go skills, Linux networking and Kubernetes (OVN-Kubernetes). Salary range stated: 184,000–287,500 USD/year.

Work on end-to-end adoption of Warp in computational applications: implement native C++/CUDA features, expose functionality via Python APIs, integrate CUDA-X libraries, and partner with internal teams to enable production use. Requires 8+ years of software development experience and substantial experience building, profiling, debugging, and optimizing performance-critical CUDA C++ software for NVIDIA GPUs, plus background in computational/scientific software and numerical methods.

Role focused on building and improving high-speed IO integration, build, simulation, and pre-submit qualification flows for large ASIC IP; improving CI reliability and debuggability; applying AI-assisted workflows; collaborating with design, verification, firmware, and infrastructure teams; and defining metrics to guide engineering priorities. Requires experience with SystemVerilog/Verilog, UVM, industry simulation/debug tools (e.g., VCS/Verdi/Xcelium), scripting (Python/Perl), and 5+ years industry experience.

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.

Develop and optimize scalable library software and numerical algorithms on modern architectures (GPU acceleration using CUDA). Collaborate with product and engineering teams, provide technical leadership, improve library performance and abstractions, and contribute to benchmarking, profiling, testing, and CI/CD practices. Requires extensive experience (12+ years) in high-performance parallel numerical applications and strong C/C++ programming skills.

Role combines ~50% customer-facing support and ~50% R&D. Responsibilities include owning Ethernet and InfiniBand adapter/DPU deployments, developing features/tools for enterprise networking products, and collaborating with engineering to reproduce and resolve issues. Requires BSc (or equivalent), 8+ years system software development and troubleshooting experience, proficiency in C/C++, strong GNU/Linux and container/Kubernetes knowledge, and experience with networking protocols (e.g., BGP, OSPF, EVPN, VXLAN). Preferred: RDMA/InfiniBand, RoCE, DPDK, DPUs, HPC (MPI/UCX).

Technical leader responsible for architecting and driving implementation of large-scale, low-latency distributed inference systems and full model lifecycle management. Requires deep expertise in GPU architecture and low-level performance tuning (CUDA, kernels), cloud-native multi-tenant model serving, orchestration (Kubernetes, Ray), and open source ecosystem engagement. Minimum 16+ years technical experience and significant leadership experience (7–10+ years cited).

Lead security engineering for RTOS, hypervisor, and embedded virtualization technologies for NVIDIA DRIVE Software. Responsibilities include collaborating on CPU/SoC architecture security, designing defensive features (partitioning, least privilege, secure updates), performing threat modeling and automotive TARA, reviewing low-level C/C++ code, building fuzzing and security test infrastructure, and driving fixes. Requires 8+ years of relevant systems/embedded/platform/automotive security experience and experience securing RTOS/hypervisor/kernel/firmware/boot/drivers; familiarity with CPU/SoC security concepts and automotive security/safety standards. Base salary ranges provided in the posting.

Lead architecture and technical strategy for DGX Cloud full-stack integration, focusing on hardware/firmware/system software interfaces, control and data plane systems, and delivering bare-metal and virtualized accelerated computing across enterprise, sovereign, and cloud datacenters. Requires extensive systems integration experience (15+ years), deep knowledge of virtualization, IaaS/PaaS, compute/storage/networking, and demonstrated technical leadership.

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 reconciling and synchronizing downstream compiler repositories with upstream open-source projects, restructuring and refactoring internal code, building automation and developer tools for rebasing/patch management/validation, applying AI-assisted tooling to developer workflows, and partnering with compiler, architecture, and CI teams. Requires a degree in CS or related field (or equivalent experience), strong C++ skills, solid compiler internals knowledge, and 3+ years working with large, long-lived codebases.

NVIDIA is hiring a Senior Deep Learning Inference Software Engineer to design, build, and optimize GPU-accelerated software and inference frameworks (vLLM, SGLang, FlashInfer). The role centers on performance tuning for LLMs, multimodal and generative AI across NVIDIA accelerators and requires strong C/C++ skills, 5+ years' software development experience, and GPU/CUDA experience. Salary ranges for Poland are provided.

NVIDIA seeks a Senior System Software Engineer for automotive performance work on Tegra/ARM platforms. Responsibilities include benchmarking and optimizing boot/runtime performance, collaborating with hardware and software teams, developing profiling tools (AI-assisted), and minimizing hypervisor overhead. Requires a Master's or equivalent and a minimum of 12 years in systems/software performance, strong C/C++ skills, experience with Linux and QNX; Android knowledge is advantageous. AI/ML experience is desirable. Location: US (remote listed); salary ranges provided in posting.

NVIDIA is hiring a Senior Software Engineer to develop and operate the Unified Access Management (UAM) platform, a policy-as-code system enforcing access control across cloud services. The role involves designing, coding, deploying features, integrating UAM with other services, and participating in on-call support. Required: BS/MS or equivalent, and 5+ years' experience (noted in ML/AI areas), with expert knowledge of AWS, Kubernetes, and GitOps and familiarity with ACL/RBAC/ABAC authorization strategies.

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.