NVIDIA seeks a Senior AI Developer Technology Engineer to research and develop GPU-acceleration and optimization techniques for AI and financial-market workloads. Responsibilities include in-depth analysis and optimization on CPU/GPU architectures, collaborating with industry and academia, and publishing findings. Requirements: advanced degree or equivalent experience, 5+ years relevant experience, strong C/C++ programming, deep understanding of algorithms and linear algebra, hands-on low-level parallel programming (CUDA, OpenACC, OpenMP, MPI, pthreads, TBB), and CPU/GPU architecture knowledge. Base salary ranges provided (USD).

Design and evaluate GPU and system architectures to improve AI inference performance and efficiency. Build power and performance models of the AI inference stack, implement and test deep learning algorithms, and collaborate across software, research, and product teams. Requires MS or PhD (or equivalent), 5+ years relevant experience, strong math foundation in ML/DL, expert programming in C/C++/Python, and familiarity with GPU computing (CUDA) and HPC (MPI/OpenMP).

New college grad (2026) position building ML and AI systems for circuit design and design automation (VLSI/ASIC/EDA). Work includes silicon data analysis, SPICE correlation, circuit optimization, design-space exploration, and integrating models with ML and visualization tools. Requires a Master's or PhD (or equivalent experience) and proficiency in Python and C++.

Work on integrating and optimizing communication libraries (NCCL, NVSHMEM, GPUDirect) into AI frameworks, perform workload and performance analysis on multi-GPU clusters, author fused compute/communication kernels, improve compiler/automation for communications, and influence communication library roadmaps. Requires 5+ years of software engineering and HPC/AI experience and strong skills in Python, C++, CUDA and deep learning frameworks.

Role focuses on developing and scaling automated inference and deployment solutions (TRT Model Optimizer) for generative AI models such as LLMs and diffusion models. Responsibilities include extracting model graph representations from PyTorch models, building optimization techniques (quantization, pruning, sharding, efficient kernels), profiling GPU performance, and architecting a modular deployment platform. Requires MS/PhD or equivalent experience and 5+ years in deep learning; strong Python, PyTorch, CUDA, and performance-analysis skills. Salary ranges provided (USD yearly).

Join NVIDIA Research Singapore to research, design and accelerate generative AI models (including LLMs, visual generation, and robotics). Responsibilities include publishing research, collaborating across teams, mentoring interns and transferring technology to product groups. Requires 2 years' experience, strong research record (publications at top conferences), proficiency in Python (prototype), and familiarity with ML frameworks such as PyTorch; C++/CUDA and parallel programming are a plus.

Work with science and research institutes in Japan to promote and deploy NVIDIA GPU-accelerated solutions for machine learning and generative AI. Responsibilities include leading research collaborations, designing architectures and demos, creating and running proofs of concept, onboarding developers to NVIDIA AI platforms (NIMs, NeMo), and presenting technical topics. Requires 5+ years' experience in generative AI/deep learning, strong coding skills (Python, C/C++, Bash, Linux), and excellent Japanese and business-level English communication.

NVIDIA seeks a Solutions Architect (Data Science) in ANZ to enable GSIs and AI consultancies on generative AI and LLM solutions (Nemo/NIMs), build GenAI full-stack solutions, run PoCs/demos, and support GPU-accelerated deployments. Requires deep expertise in generative AI/LLMs, ML/DL frameworks, Python, GPU/parallel computing, container orchestration and 5+ years' related experience.

Researches and develops techniques to accelerate deep learning, machine learning, and AI workloads on modern CPU and GPU architectures. Works with developers and researchers to analyze and optimize complex algorithms, publish findings, and influence hardware and software design. Requires a Masters (or equivalent) and 8+ years of relevant experience with C/C++, CUDA and parallel programming frameworks.

Responsible for designing, implementing, and optimizing high-performance dense linear algebra software on GPUs, leading projects and mentoring engineers. Requires 8+ years experience, a degree in CS/Applied Math or equivalent, strong C++ skills, expertise in kernel generation and JIT, and experience with GPU-related technologies (CUDA) and performance optimization. Base salary range shown: $184,000–$356,500 depending on level.

Work on communication libraries (e.g., NCCL, NVSHMEM, UCX) and co-design HW/SW solutions to accelerate AI and HPC workloads. Responsibilities include designing and implementing communication technologies, building proofs-of-concept, running experiments and simulations of large GPU clusters. Requires M.S./Ph.D. or equivalent, 5+ years' relevant experience, strong C/C++ skills, experience with parallel programming models and communication runtimes, and solid knowledge of Linux, system and network architecture.

Work on JAX core design and performance optimizations for NVIDIA products, collaborating with AI researchers and cross-functional teams. Requires BS or equivalent and 6+ years' relevant experience, proficiency in C/C++ and Python, familiarity with ML frameworks (e.g., PyTorch, TensorFlow), and strong knowledge of CPU/GPU architectures and distributed training. Base salary ranges provided: 184,000–356,500 USD/year depending on level.

NVIDIA seeks a Senior Software Architect for an applied research team building systems-level software to move data between GPUs, nodes, and storage. The role requires 12+ years in systems software and/or networking, expertise in RDMA/InfiniBand/GPUDirect/NVLink, strong C++/Rust skills, and experience with ML system concepts and inference frameworks. Responsibilities include architecting communication libraries, profiling and optimizing data movement, integrating networking into AI stacks, and contributing to open-source projects.

NVIDIA is hiring a research scientist to design and implement AI algorithms and models for general-purpose humanoid robots and embodied agents, develop large-scale training and inference methods, and optimize/deploy models in simulation and on robot hardware. Requires PhD (or equivalent), strong engineering and prototyping skills (PyTorch/JAX/TensorFlow), Python or C++, and experience with LLMs/multimodal/foundation models and/or robot learning and simulation frameworks. Position is US (remote) with Santa Clara listed; salary ranges are provided in the posting.

NVIDIA is hiring a Principal Deep Learning Algorithm Engineer to research and implement inference algorithms, profile and optimize agentic LLM workloads to reduce latency and increase throughput, and design scalable datacenter systems. Requires BS/MS/PhD or equivalent and 15+ years in deep learning/systems, strong Python and C++ skills, and knowledge of computer architecture and GPU/parallel computing. Role is listed as US (Santa Clara) with remote options and a base salary range of 272,000–431,250 USD per year.

Senior role to develop scalable library software and optimize high-performance parallel numerical applications across CPU and GPU (CUDA). Requires 5+ years experience, strong C/C++ and software-development skills, performance tuning, benchmarking, and collaboration across distributed teams. Python and familiarity with CI/CD and profiling tools are desirable.

Role involves understanding, profiling, and optimizing DL training and inference on state-of-the-art hardware; collaborating across research and engineering teams; implementing production-quality software and building automation tools. Requires 5+ years experience, strong DL and computer-architecture background, and programming skills in C++ and Python; GPU programming (CUDA/OpenCL) and LLM framework experience are advantageous.