NVIDIA seeks a Senior Architect for Data Processing Systems in Analytics & Data Intelligence to drive hardware-software co-design, full-stack performance optimization, benchmarking, and workload analysis across CPU/GPU platforms. Requires MS/PhD or equivalent and 8+ years in distributed data platforms, systems engineering, performance architecture, or related areas.

Seeking a Senior System Verification Engineer with 12+ years' experience in mixed-signal simulation or PCB design to develop verification strategies, simulation models, and pre-silicon verification environments. Requires Verilog RTL experience, Python programming, SPICE/mixed-signal simulation skills, and collaboration with architecture, ASIC, FPGA, software, and system teams. Position based in the US (Austin) with remote options; salary range listed.

Join NVIDIA Hardware Infrastructure to design and implement scalable distributed storage management systems. Role involves collaborating with hardware and software teams, developing in Perl and Python, optimizing workflows, and applying storage concepts (volumes, snapshots, clones, deduplication). Requires Linux development experience and 5+ years of relevant experience; MS preferred. Salary ranges provided by location and level.

Role involves understanding, modifying and improving an NVIDIA proprietary GPU compiler backend in C++; designing and implementing compiler passes and optimizations; and collaborating with global compiler, hardware and application teams. Requires 4+ years of compiler code generation experience and strong C++ skills. Expected base salary range: 152,000–241,500 USD per year.

Join an AI networking acceleration team to develop a performance-oriented, open-source inference framework for large data centers and supercomputers. Requires 6+ years experience in C++/C/Rust, Linux, deep knowledge of TCP/IP, and expertise in low-level performance optimizations; CUDA, RDMA, HPC and ML framework experience are advantages.

Lead measurement and analysis of coding-model performance and design/implement post-training pipelines (SFT, RL, reward modeling) to improve code generation and software-engineering capabilities. Requires a Bachelor's (or equivalent) and 12+ years' experience, strong Python skills, expertise with LLMs/transformers, and knowledge of reinforcement learning and software engineering. Location indicated as US (Santa Clara) with remote options; stated base salary ranges USD 224,000–431,250.

Join NVIDIA Halos as a Senior Software Safety Engineer to specify, implement, and verify safety requirements across software and hardware for AI-based autonomous systems (automotive and robotics). The role involves system and component safety analyses (FTA, FMEA, DFA, CCF, STPA, HARA), producing safety plans and safety case documentation, engaging with certification bodies, and applying AI safety methods. Requires a BS/MS/PhD or equivalent and 12+ years of relevant experience.

Role focuses on building automation and operational tooling for bare-metal NVIDIA GPU infrastructure (NVL72, BlueField DPUs) to move capacity into IaaS production (BMaaS/VMaaS). Responsibilities include provisioning, firmware/driver management, BMC/Redfish integration, debugging across hardware/OS/networking/Kubernetes, on-call incident response, and cross-team coordination. Requires 8+ years of production infrastructure software or operations experience and strong Go or Python skills.

NVIDIA seeks a Senior Deep Learning Software Engineer to develop and scale automated inference and deployment solutions (TRT Model Optimizer). The role involves working with PyTorch/Torch 2.0 tooling, HuggingFace, GPU kernel-level performance analysis and high-performance optimization techniques (quantization, pruning, sharding, parallelism) for LLMs and diffusion models. Requires advanced deep learning experience and strong software engineering skills.

Work on automation and operational tooling to provision, validate, upgrade, repair, and manage lifecycle of bare-metal NVIDIA GPU systems and DPUs. Requires 8+ years of production infrastructure experience, strong Go or Python skills, hands-on experience with BMC/Redfish, NVL72 systems and BlueField-3+ DPUs, Linux, firmware/driver management, network boot, on-call incident handling, and cross-team collaboration.

Own an internal product that measures, tracks, and reports open-source readiness across the DSX OS portfolio. Responsibilities include running the platform in production, automating scoring and integrations, building self-serve onboarding feedback, capturing engineering feedback, and automating readiness tracking and reporting. Requires 8+ years of relevant experience and hands-on experience with production reliability, automation, and agentic coding tools.

Role involves Linux kernel-level programming and development of networking drivers for NVIDIA ConnectX and BlueField adapters, contributing to upstream open-source kernel, debugging complex cross-team issues, and driving end-to-end engineering from requirements through post-GA support. Requires 8+ years' experience, native C skills, deep networking and kernel internals knowledge, and strong problem-solving and communication abilities.

Work on the CUDA Tile team to design and implement compiler transformations, MLIR-based dialects and lowering passes, and optimize tile-based kernels for NVIDIA GPU and LPU architectures. Requires 3+ years experience in compiler optimization, IR design, and strong C/C++ skills; familiarity with MLIR, LLVM, XLA, TVM, CUDA and GPU architecture is a plus.

Design, train, and optimize ML models for LiDAR/camera perception and multi-sensor fusion; build end-to-end ML workflows and productize models in C++ for the NVIDIA DRIVE AV platform. Requires MS/PhD or equivalent, 8+ years industry experience applying ML to perception, experience with PyTorch/TensorFlow, and proven productionization of ML models. Listed base salary ranges from 184,000–356,500 USD depending on level.

NVIDIA seeks a senior engineer to design and train large-scale models (LLM/VLM/VLA), build and fine-tune models for deployment in production autonomous vehicles and robotics, integrate ML with vehicle firmware, and work on data generation and model optimization for real-time, safety-critical systems. Candidates should have strong Python and C++ skills, experience deploying production-grade ML, and advanced deep learning expertise.

Join NVIDIA to enable CUDA Math Libraries (e.g., cuBLAS, cuSPARSE, cuSOLVER, cuFFT) on emerging and specialized platforms. Responsibilities include platform integration, defect triage, performance target identification and testing, and collaborating with CI/CD and build/test teams. Requires advanced degree or equivalent experience and 5+ years developing high-performance numerical software using C++ and Python, with strong numerical methods and parallel programming experience.

NVIDIA seeks a Senior System Software Engineer to develop and optimize Rust- and Python-based GPU-accelerated pipelines for indexing, deduplicating, filtering, and classifying multimodal datasets to support LLM/VLM training and Agentic Retrieval. The role requires 6+ years experience, hands-on MLOps and cloud familiarity (containers, Docker-Compose, Kubernetes), and expertise in LLM/VLM/Generative AI workflows, benchmarking, profiling, and performance optimization.

Lead technical vision and roadmap for 3D obstacle perception using multi-camera and multi-sensor fusion (camera, radar, lidar), design and productionize transformer- and CNN-based models (including BEV approaches), drive data and labeling strategy, define KPI frameworks, optimize for safety/latency/resource constraints, and mentor engineers. Requires 15+ years experience and proficiency with frameworks such as PyTorch, plus strong software skills in Python/C++ and CUDA.

Responsible for architecture, design, and implementation of production-grade 3D obstacle perception pipelines (multi-camera and multi-sensor fusion) using modern CNN and transformer techniques. Work includes model development, large-scale training and evaluation, data and labeling strategy, collaboration with safety/systems teams, and optimization for deployment (including CUDA/GPU work). Minimum experience ranges provided by degree (PhD 4+, MS 6+, BS 8+).

Role entails architecture and roadmap for radar-based 3D obstacle perception, research and model design (transformers, radar point clouds, BEV), sensor evaluation and integration, production-grade deep learning (PyTorch/CUDA), KPI/error analysis, and data/auto-labeling strategy. Requires 12+ years of relevant experience.