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Data Science Software EngineerState Street's Bionics team has the mission to explore, enable and exploit artificial intelligence, machine learning, natural language processing,puter vision and cognitiveputing at scale for multiple use cases across Global Delivery, Global Advisors, Global Markets, and Global Exchange business lines.
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Our mission is to build great products that accelerate next-generation computing experiences - the building blocks for the data center, artificial intelligence, PCs, gaming and embedded.
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In the ever-evolving landscape of artificial intelligence, we are a powerhouse – a cutting-edge 'AI Software Solutions Team'. Machine Learning Engineer, AI Software Solutions THE GROUP: AI is defining the next era of computing, and this is just the beginning.
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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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Algorithms, Machine Learning, Compilers, Computer Architecture, Data Mining, High Performance Computing, Distributed Systems, Data Structures, Natural Language Processing, Artificial Intelligence, Object Oriented Design, Network Security, Big Data, Web/Mobile Technologies, Operating Systems, Database Systems, Cloud Computing, Parallel Programming, Compilers, High performance Computing.
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SiFive’s unrivaled compute platforms are continuing to enable leading technology companies around the world to innovate, optimize and deliver the most advanced solutions of tomorrow across every market segment of chip design, including artificial intelligence, machine learning, automotive, data center, mobile, and consumer.
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12+ years of experience in working with the modern server architectures includes understanding of GPU, Artificial Intelligence hardware, Memory or CPU and methods for failure analysis, debugging or validation.
$133,600 - $282,200 a yearFull-timeExpandApply NowActive JobUpdated 15 days ago - UpvoteDownvoteShare Job
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Eagerness to learn and grow as a CPU cache array and DFT design engineer. We are looking for an experienced VLSI ATPG design engineer to join this innovative team as a technical expert.
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DISCO provides a cloud-native, artificial intelligence-powered legal solution that simplifies ediscovery, legal document review and case management for enterprises, law firms, legal services providers and governments.
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Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment. What sets the QA Engineer apart is a specialization in tech, automation and data, a focus on larger scope strategy, independence and confidence coordinating between disciplines and a passion for creating new and exciting products.
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You must have deep technical experience working with technologies related to artificial intelligence, machine learning and/or deep learning. Publications or presentation in recognized Machine Learning, Deep Learning and Data Mining journals/conferences.
$125,000 - $210,000 a yearFull-timeExpandApply NowActive JobUpdated 10 days ago - UpvoteDownvoteShare Job
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SGS is seeking an innovative Machine Learning Engineer to join our team and help create the next generation of analytics and artificial intelligence solutions for government and defense applications.
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We engineer business outcomes for Fortune 500 companies and digital natives in the technology, healthcare, insurance, travel, telecom, and retail & CPG industries using technologies such as cloud, microservices, automation, IoT, and artificial intelligence.
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Collaborate closely with the Data Engineering and our Artificial Intelligence and Machine Learning teams to ensure seamless adoption of traditional ML and Large Language Models into our products.
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Who we area: At Synopsys, we're at the heart of the innovations ushering the Era of Smart Everything, ranging from self-driving cars, Artificial Intelligence, Cloud, 5G and IoT. Chip design today is more complex than ever as it needs to accurately model silicon behavior at vanishingly small geometries while handling large designs with hundreds of millions of logic gates.
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