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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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Having experience with productizing machine learning models within a cloud service (e.g., AWS, Azure, GCP) and data science environments (e.g., Databricks) is a plus. You also have opportunities to research and develop applications in applied artificial intelligence using computer vision, natural language processing (NLP) and large language models (LLM.
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AI and Machine Learning: Utilize state-of-the-art AI and machine learning techniques, including natural language processing (NLP), to train the chatbot for accurate and effective communication.
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The team uses emerging technologies and methods such as data fabric, machine learning, GenAI, NLP, computer vision, artificial intelligence automation, big data analytics, and cloud native application development to drive innovation, operational efficiency, and provide the data product excellence our customers have come to value and trust us for.
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This may also include patent work related to image processing, databases, access management, natural language processing/understanding (NLP/NLU), and autonomous machines/vehicles.
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Responsibilities: Developing and training machine learning models using Natural Language Processing (NLP) techniques. Requirements: Advanced degree (Ph. D. preferred) in a field like Applied Linguistics, Computational Linguistics, or Data Science, with a focus on building and deploying machine learning models for text analysis.
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Exceptional programming skills in Python, with popular deep learning and natural language processing (NLP) tools and libraries, including Scikit-learn, Pandas, PyTorch, TensorFlow, or other leading deep learning frameworks, NLTK and spaCy for natural language processing tasks.
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The initiatives will include both short-term and long-term research in areas such as artificial intelligence, machine learning & data mining, natural language processing, big data systems, information and data visualization, and social & cognitive science.
$199,300 - $247,500ExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Hands-on experience with at least one cloud platform (AWS or Google Cloud) and at least one modern big data product such as Databricks, Snowflake, and BigQuery. We have a fast-growing team that’s distributed around the world, with offices in San Francisco and New York City. Our team has years of experience building and operating business-critical machine learning systems at leading tech companies like Uber, Google, Meta, Airbnb, Lyft, and Twitter.
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You will be responsible for developing, validating, and implementing cutting-edge machine learning algorithms, including use of Large Language Models (LLM) applied to diverse healthcare data sources, e.g. electronic medical records and to generate medical reports.
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Master focused in Computer Science / Machine Learning or related field Experience working with Google Cloud platform(GCP) - specifically Google Kubernetes engine, Terraform, and infrastructure Experience in programming concepts such as Paired Programming, Test Driven Development, etc.
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Data science techniques such as predictive analytics, machine learning, natural language processing and business intelligence, including use of big and non-tabular data.
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Natural Language Processing (NLP), Recommender Systems and/or Information Retrieval, and/or Reinforcement Learning. Data science, machine learning, optimization models, Master’s degree in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Successful completion of one or more assessments in Python, Spark, Scala, or R, Using open source frameworks (for example, scikit learn, tensorflow, torch)Doctorate, Masters: Artificial Intelligence.
$117,000 - $234,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Experience with data processing (e.g., Spark, BigQuery, DataProc), storage (e.g., S3, Google Cloud Storage), transport (e.g., Kafka, PubSub), and orchestration (e.g., Airflow, Luigi.
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We are on the forefront of CBRN defense and we are looking for talented Data Scientists that have applied experience in the fields of artificial intelligence, machine learning and/or natural language processing to join our team.
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