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Join us in developing the CUDA Quantum platform for programming powerful hybrid quantum-classical multi-processor systems. Contributing to the development of CUDA Quantum by enabling performance optimizations and GPU acceleration within the compiler and runtime.
$180,000 - $339,250 a yearFull-timeExpandApply NowActive JobUpdated 7 days ago - UpvoteDownvoteShare Job
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Linear and Nonlinear Optimization techniques, CUDA/GPU Programming frameworks (e.g., TensorFlow), and Data Analysis and Visualization tools. KLA is a global leader in diversified electronics for the semiconductor manufacturing ecosystem.
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Expert in CUDA/ CuTe , NCCL, OpenCL , Triton. Non-sales roles starting salaries are expressed as base salary and short-term incentives are in the form of the Annual Incentive Plan (AIP). Expert in CUDA/ CuTe , NCCL, OpenCL , Triton.
$205,900 - $407,500 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Experiences in in-depth CUDA programming and performance tuning (cutlass, triton). The team builds heterogeneous ML training and inference systems based on GPU and AI chips and advances the state-of-the-art of ML systems technology to accelerate models such as stable diffusion and LLM. The team is also responsible for research and development of hardware acceleration technologies for AI and cloud computing, via technologies such as distributed systems, compilers, HPC, and RDMA networking.
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And parallel programming (e.g., CUDA) is a plus. NVIDIA is searching for world-class researchers in deep learning and natural language processing (NLP) to join our applied deep learning research team which pioneered the.
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Expertise in Python and Python libraries for ML: PyTorch, JAX, DeepSpeed, PyTorch LightningHW implementation of AI acceleration (eg: writing high performance CUDA/C. 3+ years of experience in below areas:Natural Language Processing (NLP)Computer vision and/or multimodal systemsPreferred Qualifications:Demonstrated ability to drive state-of-the-art AI research with publications in Tier-1 venues such as AAAI, NeurIPS, ICLR, ACL, CVPR, ICML, EMNLP, ICCV, ECCVExperience with Multimodal AI Systems including but not limited to multimodal transformers, multimodal language models, diffusion models, speech, and audio models.
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Work experience with GPU computing (CUDA, OpenCL, OpenACC) and HPC (MPI, OpenMP) is a huge plus. Today, a self-driving car powered by AI can meander through a country road at night and find its way.
$176,000 - $414,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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PREFERRED EXPERIENCE: Experience with deep learning models and associated AI frameworks (PyTorch, TensorFlow, Jax, Deepspeed, Mosaic, Horovod, Collasal.ai) Experience with GPU kernel programming using CUDA, HIP or OpenCL. Experience in implementing and optimizing parallel methods on GPU accelerators (NCCL/RCCL, OpenMP, MPI) Experience training models in a clustered environment Experience deploying inferencing models.
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We collaborate with a broad cross section of teams at NVIDIA ranging from DL research teams to CUDA Kernel and DL Framework development teams, to Silicon Architecture Teams. Prior experience with performance aspects of Operating system intrinsics (e.g.: Linux scheduling), GPU kernels (CUDA), or DL Frameworks (PyTorch, TensorFlow.
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Understanding of GPU architecture and Nvidia software stack (NCCL, CUDA). Understanding of GPU architecture and Nvidia software stack (NCCL, CUDA). We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day.
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We seek a highly skilled MATLAB to CUDA Code Conversion Specialist to join our dynamic team and assist us in converting LTE Toolbox functions to C/C. Develop strategies to convert MATLAB LTE Toolbox code to optimized CUDA code.
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Strong experience with data science tools including Python scripting, CUDA, numpy, scipy, matplotlib, scikit-learn, bash scripting and Linux environment. Strong experience with data science tools including Python scripting, CUDA, numpy, scipy, matplotlib, scikit-learn, bash scripting and Linux environment.
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Experience with OpenCL, CUDA, or ROCm is a plus. Experience or knowledge of server firmware/BIOS settings, boot process, server monitoring and management SW. You will be working directly with key external OEM partners, field application teams, internal development teams, and other stakeholders to bring a portfolio of next-generation Server Platforms to market using AMD's Instinct Accelerators and support them post-production.
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Experience with CUDA and Deep Learning Software Stack. Experience with CUDA and Deep Learning Software Stack. NVIDIA's Deep Learning Optimized Frameworks Group is looking for an excellent DevOps Engineer to enable the next wave of NVIDIA’s highest performing deep learning software stacks.
$128,000 - $247,250 a yearFull-timeExpandApply NowActive JobUpdated 2 days ago - UpvoteDownvoteShare Job
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Excellent software skills in common ML tools such as Python, PyTorch or TensorFlow; experience implementing custom ops in CUDA is a plus. Excellent software skills in common ML tools such as Python, PyTorch or TensorFlow; experience implementing custom ops in CUDA is a plus.
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cuda job in San Jose, CA
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