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Master's degree in Electrical Engineering, Computer Engineering, or related fields with courses work in Digital Signal Processing, Image Processing, Computer Vision, Data Structures, Pattern Recognition, Machine Learning.
$126,984 - $130,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Research and apply emerging forms of statistical, machine learning (neural networks / deep networks, ensemble methods, natural language processing, computer vision) and engineering methods to Royal Caribbean Cruise Lines, data science and AI ecosystem.
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Python ecosystem preferred, R will be acceptable, machine learning libraries & frameworks (e.g. TensorFlow, PyTorch, scikit-learn) and familiar with data processing and visualization tools (e.g., SQL, Tableau, Power BI.
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Bachelor’s degree AND minimum 6 months experience using one or more of the following: natural language processing (NLP), artificial intelligence techniques, or machine learning in an academic setting (project/internship/lab.
$63,200 - $169,800 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Tasking will be assigned to leverage the existing skills of the candidate, to include physics-based modeling, application of advanced mathematical techniques for data processing, digital signal processing, image processing, signals analysis, radar system modeling, and radar performance prediction.
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The ISR Division's projects focus on advanced signal processing, adaptive sensor technologies, advanced algorithms, machine learning, and modeling and simulation for applications that include airborne radar, electronic warfare, and undersea systems.
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Our researchers have a broad range of expertise related to computer science and electrical engineering, such as AI/ML, algorithms, digital signal processing, audio engineering, image processing, computer vision, data science & analytics, distributed systems, cloud, edge & mobile computing, computer networking, and IoT.
$129,700 - $158,500 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Use analytic methods and advanced knowledge in machine learning, statistics, text mining, natural language processing, computational semantics, computer vision, and data science to develop creative solutions to complex real-world problems.
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We are interested in a variety of topics including data visualization and interactivity, applied machine learning and AI, AI bias and trust, big graphs, natural language processing, data mining, big data management, and heterogenous data analytics.
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3+ years of research experience in natural language processing, machine learning, and related fields. As a part of the global research, our AI research in Silicon Valley focuses on Foundation Models, Big Data Visual Analytics, Explainable AI (XAI), Natural Language Processing, 3D Perception & Mixed Reality, Cloud Robotics, Data Science, AI Platform, Time-series Analysis.
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Demonstrated 4+ years' hands-on experience with Python, SQL, Natural Language Processing (NLP), Large Language Model (LLM), TensorFlow/Pyspark/ or Keras is highly preferred.
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Querying, algorithms, data engineering, natural language processing, engine recommendation, experimentation, programming, data storytelling and intelligence, predictive modeling, and machine learning.
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Solid experience working with large datasets and developing ML/AI systems such as: natural language processing, speech/text/image recognition, supervised and unsupervised learning models, forecasting and/or econometric time series models.
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Find even more open roles in Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), Computer Vision (CV), Data Engineering, Data Analytics, Big Data, and Data Science in general - ordered by popularity of job title or skills, toolset and products used - below.
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You have experience in one or more of the following : - recommender systems, predictive modeling, reinforcement learning (e.g., multi-armed bandits), personalized search, computational optimization, natural language processing, deep learning, causal inference especially as applied to e-commerce/marketplaces/email marketing.
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