NVIDIA role to develop use cases and system requirements for Level 3/4 autonomous driving products, perform system-level analysis and performance budgeting, define test strategies and metrics, and drive safety and validation (SOTIF, ISO 26262). Requires MS/PhD or equivalent, 8+ years in safety-critical systems engineering, strong software development skills (Python, C++, SQL), and experience with large-scale datasets and validation processes.

NVIDIA seeks a Senior Backend Compiler Engineer to design and implement an LLVM-based JIT compiler targeting NVIDIA GPUs, develop compiler passes and optimizations, and collaborate with hardware and application teams. Requires 4+ years compiler development experience, 3+ years with LLVM, strong C++ skills, and expertise in code generation topics such as instruction scheduling, register allocation, GlobalISel, TableGen, and MIR.

NVIDIA is hiring a Senior Compiler Engineer for its Deep Learning & AI Compiler (DLC) team to analyze deep learning networks, develop compiler optimization algorithms, and collaborate with software framework and GPU architecture teams. The role requires 3+ years of relevant work or research experience, strong C/C++ and Python skills, and experience with compiler technologies such as MLIR, LLVM, XLA, or Triton; GPU/CUDA experience and deep learning framework knowledge (PyTorch, JAX) are listed as advantages.

NVIDIA is hiring a Senior Machine Learning Applications and Compiler Engineer to build and maintain high-performance runtime and compiler components for the LPX inference stack. Responsibilities include mapping large-scale inference workloads to NVIDIA systems, extending software ecosystem libraries and tooling, benchmarking and profiling for performance, and collaborating with hardware architects. Requires MS/PhD (or equivalent) with 6 years relevant experience, strong systems programming skills (C/C++ and/or Rust), compiler/runtime development experience (IR design, passes, code generation), familiarity with LLVM/MLIR, and experience with TensorFlow, PyTorch, and ONNX.

Join NVIDIA's Architecture Modeling group to model GPU architecture and baseboard components, develop and validate functional and performance simulation models, build tests and testing infrastructure, and improve the simulation platform. Requires 5+ years' relevant experience, strong C/C++ and scripting skills (Python/Perl), SystemC/TLM modeling experience, and familiarity with ML frameworks such as PyTorch and TensorFlow.

Research and develop techniques to accelerate database and data analytics workloads on NVIDIA CPU platforms; perform in-depth performance analysis and optimizations, collaborate with internal teams and external experts, and publish findings. Requires a MS/PhD or equivalent, 5+ years relevant experience, expert knowledge of modern CPU architectures (ARM, x86), low-level parallel programming, and fluency in C/C++.

NVIDIA is hiring a Raytracing Compiler Engineer to guide the design and implementation of a new LLVM-based backend JIT compiler for NVIDIA GPUs. Responsibilities include designing compiler passes and optimizations, collaborating with global compiler/hardware/application teams, and applying modern compiler technologies. Requires B.S. or higher (or equivalent), 12+ years compiler development experience including 3+ years with LLVM and code generation, and strong C++ skills. Role is based in the US with multiple listed locations and remote options. Posted salary ranges in the listing: USD 224,000–356,500 (Level 5) and USD 272,000–431,250 (Level 6).

Role involves performance characterization and root-cause analysis of multi-GPU and multi-node clusters, evaluating and implementing solutions in communication libraries (e.g., NCCL, UCX, NVSHMEM). Requires 3+ years in parallel programming and experience with communication runtimes, C/C++, Python, and HPC networking and tooling.

NVIDIA seeks a Senior Deep Learning Performance Architect to develop GPU and system architectures, build power and performance models for AI inference, construct and evaluate deep learning algorithms, and collaborate across software, research, and product teams. Requires MS/PhD or equivalent, 5+ years' relevant experience, strong ML/math foundation, expert programming in C/C++/Python, and familiarity with GPU computing (CUDA) and HPC (MPI/OpenMP).

Role involves building high-performance compiler and runtime components to map large-scale neural network inference workloads to NVIDIA platforms. Requires hands-on experience with compiler/runtime development (LLVM/MLIR), systems-level programming (C++/Rust), deep learning frameworks (TensorFlow/PyTorch/ONNX), and performance profiling/optimization. Minimum 5 years relevant experience and MS/PhD or equivalent experience.

NVIDIA is hiring a Senior Machine Learning Applications and Compiler Engineer for the LPX inference and compiler stack. The role involves building and maintaining compiler and runtime components, implementing mappings of large-scale inference workloads, extending NVIDIA software ecosystem, and collaborating with hardware teams. Required: MS/PhD or equivalent with 5 years' relevant experience, strong systems programming (C++/Rust), compiler/runtime experience (LLVM/MLIR), and familiarity with TensorFlow/PyTorch/ONNX.

Work on infrastructure software and tools to improve efficiency and resiliency for large-scale pre-training, post-training, and inference. Requires 8+ years building software infrastructure for large-scale AI systems, proficiency in Python/C/C++, experience with observability stacks (e.g., ELK, Prometheus, Loki), distributed systems, debugging/root-cause analysis, and familiarity with RDMA/NCCL/ucx/libfabrics and deep learning frameworks (PyTorch, TensorFlow, JAX, Ray).

Principal engineering role to define and drive end-to-end software architecture for NVIDIA rack-scale systems (firmware, kernel drivers, OS, networking, fabrics, user-mode drivers, and manageability). Engage with component teams, vendors, and hyperscale customers; define requirements and roadmaps; mentor architects and make key technical decisions. Requires 15+ years' experience in system architecture and deep familiarity with networking protocols, accelerator system software, management standards (Redfish/IPMI), and platform security.

NVIDIA seeks a Senior Product Engineer on the Board Product Engineering team to drive product engineering implementation, manufacturing methods, yield and quality goals, product change control, and failure debug across global contract manufacturer (CM) sites. Role requires 5+ years in product development or backend manufacturing, strong hardware/embedded and software knowledge, and proficiency in English (Chinese beneficial).

Work with NCCL, NVSHMEM and related technologies to integrate new communication features into AI frameworks (PyTorch, JAX, TRT-LLM, vLLM, SGLang), perform workload and performance analysis on multi‑GPU clusters, author fused compute-communication kernels, and influence communication library roadmaps. Requires 8+ years of software engineering and HPC/AI experience and proficiency with Python, C++, CUDA and performance tooling.

Join NVIDIA's Quantum Computing team to collaborate with product, research, engineering teams and external partners to develop real-time quantum error correction and calibration, distill product requirements across hardware, software and firmware, and create and review test cases. Requires a bachelor’s (or equivalent) and 5+ years post-bachelor’s experience with hands-on work on real qubits and quantum control systems.

NVIDIA seeks a Senior Systems Software Engineer to lead performance practices for large-scale GPU infrastructure and AI workloads. The role involves system composition and tuning, debugging firmware/software performance issues, collaborating with HW/FW/SW teams (BMC/SBIOS/OS/drivers), and developing tools and methodologies for HPC and cloud/container-based environments. Requires strong experience with CUDA, Linux, container tech, C/C++/Python/Bash and 8+ years of applicable experience.

Responsible for designing and implementing new NIC/DPU firmware features and protocols across product life stages, from pre-silicon to launch. Requires 5+ years C/C++ experience (embedded systems, binary network protocols), advanced English (C1), familiarity with Git/Gerrit, Linux, Bash/Python, and experience with test automation and debugging.

Work on a performance-oriented, low-level inference infrastructure using hardware offloads (GPU kernels, CUDA) and RDMA network cards. Requirements include ~8 years in modern C++/C/Rust development, ~3 years in Linux development, deep knowledge of TCP/IP, computer architecture and OS concepts. Advantages include experience with LLM inference stacks, distributed storage, Linux internals, low-level optimizations, parallel programming, HPC and RDMA.

Develop and maintain automated verification for high-end hardware and software storage solutions, collaborating with R&D to improve test coverage, performance, quality and stability. Requires 2+ years scripting (Python/Bash) and Linux experience, familiarity with networking and QA automation; English (Upper-Intermediate/B2).