Join NVIDIA's Infrastructure Specialists team to set up and validate multi-GPU/multi-node Linux GPU clusters, run and analyze AI/LLM benchmarks, improve collectives and NCCL usage (AllReduce, AllToAll), build observability and automation (Python, Shell), and collaborate across hardware, software, networking, and product teams to prepare AI factories for customers.

NVIDIA seeks a Developer Relations Manager to engage ISVs, primes, and drone OEMs on GPU-accelerated autonomy stacks (Jetson, Holoscan, Isaac, CUDA-X) for uncrewed systems. The role requires deep technical experience in robotics, onboard autonomy, perception, sensor fusion, and production deployments on SWaP-constrained airborne platforms; candidates must be U.S. citizens.

NVIDIA is hiring a Principal Systems Software Engineer to work on custom CEF and Chromium code for GeForce NOW client platforms. Responsibilities include improving performance, reliability, cross-platform compatibility, security, CI/CD and patching infrastructure, and upstreaming applicable changes. The role requires 15+ years' experience, strong C++ and JavaScript skills, and a history of contributions to Chromium or CEF repositories.

NVIDIA is hiring a Senior Backend Compiler Engineer to understand, modify, and improve a proprietary GPU compiler backend written in C++. Responsibilities include designing and developing register allocation passes and other optimizations, working with global compiler, hardware, and application teams, and supporting deep-learning compiler technology. Requires 3+ years of compiler code generation experience (preferably LLVM); MS/PhD is highly desired. Base salary range: 152,000 USD - 241,500 USD per year.

Role based in Singapore (remote possible). Serve as technical SME for NVIDIA technologies, lead strategic engagements with academia/industry/government, mentor junior engineers and students, develop tutorials/demos/workshops, and support AI ecosystem initiatives. Requires a PhD or equivalent experience in AI-related research, 5+ years working with NVIDIA technologies, strong Python and PyTorch proficiency, and expertise in areas such as digital twins, synthetic data, immersive multimedia, and generative AI.

Lead research and engineering engagements in AI for Chemistry and Materials Science, acting as a technical SME for NVIDIA technologies (e.g., ALCHEMI, CUDA-X). Responsibilities include collaboration with academia and industry, mentoring junior staff and students, developing tutorials/demos/workshops, and advancing ML-based methods such as MLIPs and generative models. Requires a PhD or equivalent and at least 5 years’ experience; proficiency in Python and PyTorch.

Lead technical engagements with NVIDIA Cloud Partners to design, build, and deliver GPU-based AI/GenAI and HPC solutions across the customer lifecycle. Requires 8+ years in solution/sales/cloud engineering, hands-on experience with deep learning frameworks (PyTorch, TensorFlow), Python, large-scale cluster/cloud architectures, model fine-tuning and deployment, and familiarity with NVIDIA stack and cloud providers.

Role focuses on developing and unifying the Triton and Dynamo inference stacks to build a high-performance GPU-accelerated AI inference platform. Requires 5+ years in deep learning software, strong Rust and C++ skills, familiarity with Python, experience with ML and high-scale distributed systems, and open-source engagement.

NVIDIA seeks a Senior Solutions Architect for Generative AI to lead customer technical engagements, develop proofs-of-concept (LLMs, recommenders), and optimize model training/inference on GPUs. Requires a BS/MS/PhD or equivalent, 8+ years as an AI/software engineer, strong coding in Python and/or C++, experience profiling and optimizing GPU performance, and experience with DL frameworks and lower-level GPU libraries (CUDA/CUTLASS/cuDNN/NCCL). The role is remote-friendly, based in the US (Santa Clara referenced), includes occasional on-site customer visits/conferences, and lists base salary ranges (USD 184,000–287,500 for Level 4; USD 224,000–356,500 for Level 5).

NVIDIA is hiring a Senior Machine Learning Compiler Engineer with 8+ years of software engineering and ML experience. The role requires strong knowledge of compilers, code generation, GPU architecture, and hands-on experience with Python, C/C++, Julia, and Lisp/Scheme. Familiarity with LLVM, reinforcement learning, evolutionary algorithms, predictive modeling, and deploying ML solutions to production or embedded systems is listed as a plus. Locations include US-based sites (Redmond, Santa Clara, Austin) and remote; base salary range: 184,000 USD - 287,500 USD per year.

Role on NVIDIA's Aerial Omniverse Digital Twin team to build CUDA GPU kernels and architect inter-cell data flows across thousands of GPUs (NVLink/NIC/RDMA). Requires 12+ years' experience, PhD or equivalent, deep expertise in CUDA, multi-device GPU systems, OFDM/5G NR channel emulation, and real-time system design. Salary ranges provided for Levels 5 and 6.

Work on GPU-accelerating high-performance database, ETL, and data analytics applications; analyze and optimize complex data-intensive workloads; influence hardware and software design with research, hardware, system software, libraries, and tools teams. Requires a Masters/PhD (or equivalent), fluency in C/C++, low-level parallel programming experience (CUDA preferred), and expertise in CPU/GPU architecture and memory subsystems.

Role involves transistor-level and system-level design of analog/mixed-signal power delivery and voltage regulation solutions, driving IP development and physical implementation, performing detailed simulations and reliability analysis, collaborating with cross-functional teams, and developing prototypes for deployment. Requires MS/PhD (or equivalent), 5+ years experience, and expertise in deep submicron processes and AMS design. Salary range stated: 168,000–264,500 USD per year.

Technical leader for GPU-accelerated AI/HPC infrastructure: design and operate on-prem and cloud clusters, build automation, support researchers, perform performance analysis and root-cause investigations. Requires 5+ years designing and operating large-scale compute infrastructure and experience with schedulers (Slurm/K8s/PBS/LSF), Linux administration, configuration management (Ansible/Puppet/Salt), container technologies, Python and MPI.

NVIDIA seeks a Senior Solutions Architect for the IPP Cloud Infrastructure team to design, implement and support end-to-end CI/CD and private GPU cloud services used by internal development teams. The role involves optimizing performance and cost of AI development/test systems, onboarding customers onto private cloud, leading software projects, and using technologies such as OpenStack, Kubernetes, Docker, VMs, Java, Python, SQL/NoSQL databases, and various DevOps tools. Requires BS in EE/CS or equivalent and 12+ years of systems software development experience (including at least 1 year with AI).

Lead a team consulting on and optimizing GPU-accelerated datacenter infrastructures, performing hands-on analysis and tuning, collaborating with engineering/product/sales and customers, and establishing monitoring and optimization methodologies. Requires experience in data center/server/network operations, strong technical leadership, and proficiency in Japanese and English.

The Senior Package Engineer will lead development of advanced microelectronics/ASIC packaging, collaborate with vendors and subcontractors, and support failure investigations, production excursions, and reliability issues. Requires an MSc or equivalent experience in Mechanical/Materials Engineering and at least 5 years developing complex processes (warpage, heat, optics, adhesives) with strong project focus and vendor collaboration experience.

Principal Architect on NVIDIA's Networking Systems & Software Architecture team responsible for setting long-term technical vision, conducting original research and prototypes (RDMA, NVLink, GPUDirect), driving hardware-software co-optimization across GPUs/DPUs/NICs, integrating networking into AI serving stacks, publishing results, and mentoring senior engineers. Requires 15+ years in systems software or networking and expertise in high-performance networking, communication libraries, GPU-accelerated systems, and languages such as C/C++/Rust/Python.

Work on RL post-training infrastructure that scales from single-GPU experimentation to production across thousands of nodes, focusing on rollout generation, training-inference loops, fault tolerance, and performance tuning. Requires expertise in distributed systems, deep learning infrastructure, PyTorch, Kubernetes, and proficiency in Python and C++.

NVIDIA seeks a senior Technical Marketing Engineer with 6+ years' experience to produce how-to content, documentation, tutorials, and EDA benchmarking that demonstrate the value of NVIDIA platforms. The role requires strong technical communication, hands-on familiarity with EDA/semiconductor tools, and knowledge of AI/ML and parallel programming techniques.