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Prototypes and do proof of concepts (PoC) in one or all the following areas: · LLM, NLP, DL (Deep Learning), Client (Machine Learning), object detection/classification, tracking, etc.
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Proven experience as a Data Scientist, with a focus on machine learning, LLM, and Deep Learning. We are seeking a talented Data Scientist with a strong focus on LLM (Large Language Models) and Deep Learning to join our team.
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Expertise as evidenced by a strong record of peer-reviewed academic publications, combined with hands-on research experience in applications of machine learning, deep learning, natural language processing and algorithms is desired.
$192,500 - $362,200 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Deep Learning Frameworks (PyTorch, TensorFlow, Jax) - Hands-on experience building, training, and optimizing deep neural networks that utilize GPUs. They should have solid knowledge of AI and machine learning concepts including deep learning, NLP, computer vision, and generative AI. Hands-on experience benchmarking, analyzing performance, debugging and optimization of hardware for AI workloads is key.
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Stay informed and integrate latest statistical modelling, machine learning, deep learning, recommender system and/or artificial intelligence trends to improve and enhance modelling stack and improve business metrics and customer experience.
$117,000 - $234,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Design, implement and maintain highly-optimized communication runtimes for Deep Learning frameworks (e.g. NCCL for TensorFlow/Pytorch) and HPC programming interfaces (e.g. UCX for MPI/OpenSHMEM) on GPU clusters.
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As a Senior Digital Design Verification Engineer at NVIDIA, you'll verify the design and implementation of our cutting edge SerDes IPs. This ground breaking technology will enable and accelerate gaming, artificial intelligence, deep learning, and autonomous driving.
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5 years of experience with machine learning algorithms and tools (e.g., TensorFlow), artificial intelligence, deep learning and/or natural language processing. - Strong sense of business insights, data-driven mental model and thinking process and hands-on data analytics experiences.
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As a Computer Scientist/Engineer on the Fraud Team, you will be at the forefront of developing and executing an innovative strategy utilizing Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL), Natural Language Processing (NLP), Large Language Models (LLM), and Multi-Agent Systems to combat a variety of fraudulent activities.
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Strong Python and deep learning development skills and experience with one or more training or deployment environments (PyTorch, Tensorflow) PhD or MS degree in Computer Science or a related technical field, with a focus on computer vision and/or machine learning.
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A minimum of 3 years of experience in developing AI, ML, DL, NLP, LLM, and/or multi-agent algorithms, with a focus on fraud detection and prevention. Non-sales roles starting salaries are expressed as base salary and short-term incentives are in the form of the Annual Incentive Plan (AIP.
$127,300 - $229,300 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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This is an opportunity to work on the most challenging data science problems, build large scale distributed machine learning systems from the ground up, and use cutting edge technologies like Spark, Kafka, and Tensorflow.
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Hands-on experience of process engineering with basic understanding of general semiconductor manufacturing flows a bonus. Collaboration with sales team on new applications or potential for future tool sales.
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Nearest Major Market: San Francisco Nearest Secondary Market: Oakland Job Segment: Cloud, Pre-Sales, Engineer, Technology, Sales, Engineering, Strategy. Specialists will develop deep sophistication with the technology behind the Spot product portfolio, and they will use that knowledge to source, close, and ramp software deals in NetApp’s Enterprise segment.
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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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deep learning hands on sales jobs Company: Apple in San Jose, CA
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