Role to research, develop, train, fine-tune, and deploy multimodal agentic AI (LLMs and audio-visual systems) with responsibilities spanning planning, tool execution, long-horizon tasks, alignment (instruction tuning, RLHF/RLVR/MOPD), dataset collection, and benchmarking. Requires MS or PhD (or equivalent) with 8+ years of relevant experience, strong Python and PyTorch skills, expertise in deep learning and reinforcement learning, and experience with large-scale distributed training and multimodal datasets.

Seeking a Senior Solutions Architect to lead technical delivery for enterprise ISV partner engagements focused on agentic AI, multi-agent orchestration, RAG, model customization, and production deployments on NVIDIA AI and GPU infrastructure. Requires 8+ years experience, strong Python/Linux skills, hands-on experience with LLMs/generative AI, PyTorch/TensorFlow, and familiarity with agent frameworks and NVIDIA tooling.

NVIDIA is hiring a Senior AI & Deep Learning Compiler Engineer to develop compiler optimization algorithms, define public APIs, and implement compiler techniques for AI workloads targeting NVIDIA GPUs. The role requires 3+ years of relevant experience, strong skills in CUDA, C/C++, Python, compiler technologies (e.g., MLIR, LLVM, XLA, Triton), and GPU performance analysis. Locations include US (Austin, Santa Clara) and remote options.

Lead technical engagements with strategic ISV partners, design and ship production agentic AI (RAG, multi-agent workflows, inference) on NVIDIA and open stacks (NeMo, TensorRT-LLM, vLLM, LangChain, vector DBs). Requires 12+ years in technical product/engineering/solutions roles, advanced AI/ML and deep learning experience, proficiency in Python and PyTorch, and familiarity with MLOps, Kubernetes, Docker, and enterprise security/compliance.

Work at the intersection of research, product, and engineering to bring agentic AI research into production: prototype and benchmark methods (LLMs, agent harnesses, multimodal models), design secure-by-default agent workflows, integrate inference and runtime infrastructure, and collaborate across teams. Requires 8+ years' experience and advanced degree or equivalent.

Hands-on role bridging hardware bring-up, sensor pipelines, and edge AI model deployment for NVIDIA Physical AI partners. Requires 5+ years in embedded systems (Jetson experience), strong ROS 2 fluency, sensor integration (cameras, LiDAR, IMU), and expertise in GPU profiling and optimization (e.g., TensorRT).

Lead development of scalable mapping and 3D reconstruction systems that transform crowdsourced camera and sensor data into high-quality maps for self-driving vehicles. Requires 15+ years experience, strong C++ production engineering skills, and expertise in 3D computer vision, multi-view geometry, pose estimation, sensor fusion, and large-scale sensor data processing.

Principal-level role in AI Networking Codesign and Benchmarking R&D to profile, analyze, and optimize AI workloads on large-scale GPU/CPU clusters. Responsibilities include benchmarking and profiling distributed systems (collective communication, networking, NCCL/RDMA/RoCE), developing PyTorch trace-based profiling and replay tooling, collaborating across hardware and software teams, and defining performance test plans.

NVIDIA seeks a Senior Scientist to develop LLM-based synthetic data generation pipelines and multimodal data (image, document, video, audio) for pre- and post-training of large models. The role combines applied research and software engineering, contributing to the NeMo ecosystem, publishing at top conferences, and mentoring junior researchers.

Work on research and engineering of AI systems for quantum system calibration and decoding, including physics-informed synthetic data generation, surrogate hardware modeling, co-optimized calibration-decoding pipelines, reinforcement/online learning for calibration policies, and GPU-accelerated implementations. Requires deep background in quantum device physics, ML/DL at scale, and 8+ years of relevant experience (PhD strongly preferred).

NVIDIA seeks a Senior AI/HPC Engineer / Solution Architect to deploy, manage, and maintain Linux-based AI/HPC infrastructure for customers. The role involves system and network design, cluster management, automation, troubleshooting, documentation and customer-facing support for large GPU clusters and AI workloads. Requires 5+ years of relevant deployment/support experience and strong Linux, networking, scheduler, and automation skills.

Senior Principal Architect in NVIDIA's Advanced Development team working on GPU Networking to optimize AI workloads. Responsibilities include leading vision, architecture, and proof-of-concept development across distributed AI, HPC, SDN, virtualization, storage and related data center technologies. Requires M.Sc. or Ph.D. (or equivalent), 8+ years industry experience in systems architecture or related fields, experience with virtualization, networking, storage, Windows and Linux drivers, and strong performance profiling and optimization skills.

NVIDIA seeks a Senior Solutions Architect (Gen AI) to work with hospitality and travel customers to design, build, and deploy agentic and generative AI solutions using NVIDIA full-stack technologies. Role requires hands-on experience with LLM training, fine-tuning, inference optimization (e.g., vLLM, TRT-LLM), GPU cluster architectures, and DevOps tools, plus customer-facing POC development, workshops, and technical enablement. Minimum 8 years experience and advanced degree preferred.

Lead technical collaborations with supercomputing centers and industry partners to develop hybrid quantum-classical applications; drive research in AI for quantum algorithms; manage execution of technical projects with QPU builders and strategic partners; publish research and represent NVIDIA at conferences; support customer adoption through strategic technical engagement. Requires PhD or equivalent, 9+ years working on quantum algorithms and applications, and demonstrated technical leadership.

NVIDIA seeks a Senior Software Engineer to design and implement performance analysis tools and workflows for AI training and inference. The role involves integrating profiling infrastructure with AI frameworks, identifying performance bottlenecks, automating detection/diagnosis, and collaborating with performance engineers, hardware architects, and software teams. Requires MS/PhD or equivalent, 6+ years' experience, deep knowledge of AI workloads, and strong software skills (Python, C++).

Role focuses on designing and implementing learning-based compiler optimization workflows, integrating LLMs with compiler infrastructure, and validating performance on representative benchmarks. Requires 8+ years experience, strong knowledge of compilers, GPU architecture, proficiency in Python and C/C++, and hands-on LLVM/MLIR experience. Salary range stated as 184,000–287,500 USD per year.

Work on the Triton compiler project to design and implement compiler technology (using MLIR) and optimize high-level kernel descriptions to generate efficient GPU code. Responsibilities include performance tuning (including inline PTX), collaborating with hardware and CUDA teams, and investigating GPU architectures and AI algorithms. Requires a degree in CS or related field and 8+ years industry experience with strong C++, parallel programming (CUDA/OpenCL), assembly-level programming, and computer architecture.

Work involves researching, implementing, and validating model and algorithm improvements for video/world generation (human appearance, motion, interaction), improving training/inference efficiency, defining training objectives and benchmarks, and translating research into production-grade checkpoints and integrations. Requires a PhD or equivalent, 8+ years applied research/industry experience, and strong hands-on skills in Python, PyTorch, C++, CUDA, and distributed training.

Role to analyze deep learning networks and develop compiler optimization algorithms for NVIDIA's Deep Learning Compiler used across data centers, devices, automotive, and robotics. Requires 3+ years relevant experience, strong C/C++ and Python skills, and experience with technologies such as MLIR, XLA, TVM, LLVM, CUDA/OpenCL and deep learning frameworks (e.g., PyTorch). Posted locations include Austin, Redmond, and Santa Clara (also remote options); stated base salary range USD 152,000–241,500.

Lead the technical vision, original research, and prototyping for distributed AI communication systems (GPU-to-GPU, GPU-to-storage, cross-node) using technologies such as RDMA, NVLink, GPUDirect and communication libraries (NCCL, UCX, MPI, NVSHMEM). Requires 15+ years in systems software/networking, strong GPU-accelerated systems and computer architecture knowledge, and proficiency in C/C++/Rust/Python.