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Job Description :We are looking for a seasoned Machine Learning Engineer specialized in Large Language Models (LLMs) to drive the development and deployment of cutting-edge AI solutions.
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In this role, you'll have the opportunity to work on cutting-edge data visualization and analysis projects, enhancing our understanding of client interactions and improving business unit segmentation.
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The ArcGIS platform is an expansive spatial data science platform, incorporating both specialized geospatial data science tools and cutting-edge open source components, helping our users develop workflows that power modern business and make the world a better place for future generations.
$194,688 a yearFull-timeExpandApply NowActive JobUpdated 21 days ago - UpvoteDownvoteShare Job
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This role offers a unique opportunity to gain hands-on experience in both traditional machine learning techniques and cutting-edge deep learning models in the context of cell biology.
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Much of our work contributes to innovative research in the fields of sensor science, signal processing, data fusion, artificial intelligence (AI), machine learning (ML), and augmented reality (AR.
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We integrate off-the-shelf and new development efforts to sustain and enhance Defense Intelligence Agency's (DIA) National Media and Exploitation Center (NMEC) architecture by leveraging cloud-based computing, artificial intelligence (AI), machine learning (ML), and cross-domain transfer systems to provide cutting-edge data exploitation, enrichment, triage, and analytics capabilities to Defense and Intelligence Community members.
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ABSC's employees – including software developers, multi-disciplined intelligence analysts, technology protection engineers, program support personnel, and specialists in cloud, data science, AI/ML, and cyber – diligently support their customers, address their challenges, and stay ahead of technological or operational impacts to the mission.
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Do you want to leverage your skills in data science and machine learning to create cutting-edge solutions that help athletes perform better and prevent injuries.
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We are looking for a Staff Machine Learning Engineer to lead the scaling and deployment of cutting-edge machine learning and deep learning models powering Data Ventures team.
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Our Fraud Intelligence team is on the cutting edge of data science and machine learning technology that detects and prevents fraud on a global scale. As a Machine Learning Data Engineer, you will tackle challenges ranging from identity theft to credit card fraud, to money laundering, and more.
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You will apply classical ML algorithms and cutting-edge deep learning (DL) approaches to areas within the natural language processing and understanding spaces including GenAI, document processing and understanding, call center analytics, and chat experiences.
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If you are excited by the opportunity to build cutting-edge machine learning models and apply your data science expertise in a dynamic sports technology environment, we’d love to hear from you.
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Leverage cutting-edge machine learning and statistical methodologies, including large language models (LLMs), deep learning, and graph neural networks, to address diverse challenges, including areas such as AI agents, order logistics prediction and optimization, robotics automation, recommendation systems, knowledge graph building and mining, etc.
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Advanced degree (PhD or Master) in Computer Science, Machine Learning, Data Mining, Statistics, or related technical field with preferred 3+ years of relevant experience. As a Machine Learning Engineer at CSS, you'll be an integral part of building out the state-of-the-art AI intelligence engine and applications for the food industry.
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As a Staff Data Engineer in our Data Science and Engineering team, you will help design, implement and manage the data platform which powers Tenstorrent’s data engineering and data science workflows, including batch processing, streaming, metadata management, and machine learning.
$500,000 a yearFull-timeExpandApply NowActive JobUpdated 1 month ago
cutting edge science machine learning jobs Title: data engineer in IN, Pennsylvania
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