Role focuses on research, implementation, and validation of model and algorithm improvements for human-centric video generation and world models. Responsibilities include prototyping spatial multimodal and neural-rendering approaches, improving training and inference efficiency, defining training objectives for sim-to-real/real-to-sim generalization, building domain-specific benchmarks, and translating research into production-grade checkpoints and integrations. Requires PhD or equivalent, 8+ years applied research/industry experience, 3+ years designing/training generative models, and advanced proficiency in Python, PyTorch, C++, and CUDA.

Build and optimize inference stacks (vLLM), develop and tune GPU kernels, extend compiler/DSL infrastructure, define benchmarking (including MLPerf), and architect containerized large-scale inference deployments. Requires strong Python and C/C++ skills, GPU/CUDA experience, familiarity with PyTorch and inference engines, container/orchestration experience, and advanced performance engineering; typical experience expectations are 7+ years (BS) or 5+ years (MS).

NVIDIA seeks a Senior Software Developer for AI Networking to develop production communication frameworks, tools and benchmarks, enable AI models in benchmarking infrastructure, and design automation systems for large-scale clusters. Requires B.Sc./M.Sc. in CS or Software Engineering and 5+ years' experience, professional Python development skills, and strong Linux/command-line expertise. Experience with PyTorch/LLMs, Slurm/Kubernetes, MPI/HPC, InfiniBand/Ethernet, and performance optimization is desirable.

NVIDIA Office of the Chief Security Officer seeks an AI Automation Engineer to design, implement, and operate agent-enabled security systems, including ETL and agentic data pipelines, MCP integrations, retrieval and coordination patterns, and governance for agent-accessible data. Requires 8+ years in automation/data engineering, experience with AI agents and MCPs, and familiarity with Python/Go/C++, AWS, Terraform, Airflow, and Databricks. Salary ranges provided (USD 168,000–270,250 for Level 4; USD 196,000–310,500 for Level 5).

Join NVIDIA's Partner Network as a Senior Solutions Architect to guide partners in adopting end-to-end AI and HPC solutions using NVIDIA compute, networking, and software stacks. The role requires 12+ years of experience with cluster management and tools such as Docker, Slurm, Kubernetes, and Ansible, plus hands-on experience with networking, storage, and GPU-based workloads.

NVIDIA seeks a Senior Solutions Architect/AI Compute Engineer to work with partners, customers, and internal teams deploying and validating Linux-based AI/HPC systems. Role requires 8+ years of deployment/support experience, expertise in Linux administration, cluster provisioning, networking, scripting (Bash/Python/Ansible), schedulers (SLURM/LSF/UGE), benchmarking (HPL/NCCL/MLPerf), Kubernetes, and up to 30% US travel.

Research and develop techniques to GPU-accelerate leading federal-ecosystem applications; perform in-depth analysis and optimization for current and next-gen GPU architectures; craft and optimize parallel algorithms and data structures; contribute reference code and software stack; collaborate with architecture, research, libraries, tools, and system software teams. Occasional travel. Salary ranges provided by level in posting.

NVIDIA is hiring a Senior HPC and AI Network Software Architect to build and evolve scalable systems for distributed AI training and real-time inference. Responsibilities include developing communication and runtime capabilities (e.g., NCCL, UCX, UCC), partnering with AI framework teams (TensorFlow, PyTorch, JAX), and collaborating on hardware/system features across GPUs, DPUs, and interconnects. Requires Ph.D. or equivalent experience, 5+ years in systems programming, parallel/distributed computing or HPC, and strong C++, Python, and GPU programming experience. Locations referenced: UK, Poland, Germany, Switzerland (Zurich) and remote.

Role to optimize inference speed and carry out production deployment of Cosmos foundation models on diverse GPU platforms; profile and remove bottlenecks in deep learning workloads. Requires 5+ years' experience, MSc/PhD or equivalent, strong deep learning background, Python and PyTorch skills, and experience with inference optimization techniques and frameworks (e.g., TensorRT, vLLM).

Join NVIDIA Research Singapore to research and design efficient generative AI and foundation models (LLMs, visual generation, robotics) optimized for NVIDIA GPUs. Responsibilities include publishing original research, collaborating with internal and external teams, mentoring interns, and transferring technology to product groups. Requires a PhD in CS or EE, ~4 years' experience, strong Python prototyping skills; C++ and CUDA and familiarity with PyTorch are a plus.

Work on designing and optimizing kernels, extensible abstractions for LLM serving engines, JIT domain-specific compilers, and inference runtimes for NVIDIA hardware. Qualifications include a Master's (PhD preferred) or equivalent experience, 6+ years in ML/DL systems development, experience with frameworks such as PyTorch/JAX/TensorFlow/ONNX, and expertise in GPU kernel development and compilers. Base salary range listed as 184,000 USD - 287,500 USD per year.

Join NVIDIA to develop AI inference systems, including kernel implementations, code generators, and runtimes to accelerate LLMs and other AI workloads. Requires a Master's (or equivalent) preferred PhD, 6+ years of ML/DL systems development experience, and strong experience with Python, C/C++, CUDA, deep learning frameworks, and GPU kernel performance optimization. Base salary range: 184,000 USD - 287,500 USD.

NVIDIA is hiring a Senior AI/HPC Engineer on the infrastructure Specialist team to deploy, manage and maintain AI/HPC GPU infrastructure in Linux environments. The role involves customer-facing architecture and implementation, cluster and network optimization (InfiniBand/Ethernet), scheduler and MPI/NCCL expertise, automation (Ansible/Salt/Puppet), Kubernetes, and documentation/knowledge transfer. Requires a related degree or equivalent and 5+ years of deployment/support experience.

Lead technical strategy and deep engagements for AI Factory networking at strategic customers, acting as principal-level authority for products such as BlueField and ConnectX and technologies including DOCA, RDMA, RoCE, and InfiniBand. Requires 15+ years of industry experience, strong low-level software skills in C/C++, system-level debugging, high-performance networking, and expertise in performance tuning, reliability, and production hardening.

NVIDIA is hiring a Senior Software Developer for an AI networking acceleration team to build a performance-oriented open-source inference framework using hardware offloads (GPU kernels, RDMA). Requires B.Sc. or equivalent and 6+ years of modern C++/C/Rust development, plus Linux experience and deep knowledge of TCP/IP, computer architecture and OS concepts. Locations listed include Czechia, Romania, Hungary and Poland (remote options). Poland base salary ranges are provided in the posting.

Role requires developing system-level requirements and performance budgets for L3/L4 autonomous driving, defining test strategies and metrics, partnering with data, test engineering, and integration teams, and applying SOTIF/functional safety (ISO 21448/ISO 26262) practices. Candidates should have 8+ years in safety-critical systems engineering, strong software development skills (Python, C++, SQL), and experience with large-scale datasets, validation, and architectural trade-offs.

Work on analyzing deep learning networks and implementing compiler optimization algorithms for AI inference across NVIDIA GPUs. Collaborate with deep learning framework and GPU architecture teams; require 3+ years relevant experience, strong C/C++ and Python skills, and experience with compiler technologies (e.g., MLIR, LLVM, XLA, Triton).

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

Role responsible for improving ML training and inference efficiency across GPU clusters by debugging and optimizing software and infrastructure, building tools and frameworks to detect bottlenecks, collaborating with researchers across domains (LLMs, robotics, autonomous vehicles, video), and working with technologies such as CUDA, NCCL, Nsight, distributed training, cloud platforms, and fast distributed storage.

Work on implementing and optimizing language and multimodal model inference in NVIDIA Inference Microservices and TRT-LLM. Requires 5+ years experience, strong deep learning and inference background, performance profiling/optimization (especially GPU), and proficiency in C++ and PyTorch.