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 on a performance-oriented, low-level inference infrastructure using hardware offloads (GPU kernels, CUDA) and RDMA network cards. Requirements include ~8 years in modern C++/C/Rust development, ~3 years in Linux development, deep knowledge of TCP/IP, computer architecture and OS concepts. Advantages include experience with LLM inference stacks, distributed storage, Linux internals, low-level optimizations, parallel programming, HPC and RDMA.

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.

Role involves architecting, developing, and operationalizing large-scale GPU-accelerated compute platforms and software stacks, working with internal and external engineering teams and researchers. Requires 8+ years' experience in accelerated computing for datacenter/HPC, programming/scripting (C/C++/Python/Bash), parallel filesystems, and strong communication and teamwork. Salary range (base) provided: 184,000–356,500 USD/year depending on level.

Role involves partnering with NVIDIA engineering, product, and sales to secure design wins; performing proof-of-concepts and in-depth profiling/optimization of ML/DL models on GPU architectures; working with client ML researchers and engineers; and producing collateral (notebooks, blogs) for finance use-cases. Requires 12+ years of relevant experience and strong Python/C++ and ML/DL framework knowledge.

Work on design and implementation of GPU-accelerated libraries and SDKs for unstructured sparsity in deep learning and HPC. Responsibilities include developing a C++ system for sparse tensor computations, DSL specifications for sparse storage formats, on-demand code generation, enabling frameworks like Python/PyTorch, and performance evaluation and optimization. Required: BS/MS/PhD (or equivalent), 6+ years developing and optimizing high-performance C++ software, strong Python and CUDA skills, and experience with parallel programming (MPI/OpenMP) and sparse compilers (MLIR or TACO).

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.

Role to partner with NVIDIA engineering, product, and sales to drive design wins in banking and consumer finance by performing proofs-of-concept, profiling and optimizing ML/DL models on NVIDIA GPUs, and building industry-specific collateral. Requires 12+ years as an ML/Software Engineer, BS/MS/PhD or equivalent experience, strong coding in Python and C++, and experience with ML/DL frameworks (TensorFlow, JAX, PyTorch, Spark, Dask). Base salary range stated: 224,000 USD - 356,500 USD per year.

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.

Role to scope, design, and implement high-performance numerical dense linear algebra software on GPUs, provide technical leadership, and work with product teams and customers. Requires a PhD or Master’s (or equivalent experience), 5+ years developing production software with CUDA and C++, strong fundamentals in finite precision arithmetic and numerical linear algebra. Locations listed: Germany, Poland, France (also remote).

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.