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Ideal candidates have a strong publication record in areas including artificial intelligence data mining, machine learning, natural language processing, and/or fields such as cognitive science, learning analytics, and psychometrics.
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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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We are interested in a variety of topics including large-scale distributed systems, stream processing, edge computing, applied machine learning and AI, big graphs, natural language processing, big data management, and heterogenous data analytics.
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Data Science & Machine Learning Engineer will be responsible for developing state-of-the-art data processing pipeline based on machine learning models and leveraging data science algorithms to parse substantial data and logs in a timely manner to automatically tackle the issues or provide recommendations for the next step of solving problems.
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What Additional Experience Makes A Strong Candidate: 4+ years of production experience with Scala 4+ years of production experience with Micro Services / Streaming Services Experience addressing ML problems, particularly in domains such as Time Series, Computer Vision (CV), Natural Language Processing (NLP), and data mining Proficiency with popular ML frameworks (Xgboost, TensorFlow, PyTorch, etc.
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We are looking for a passionate, talented, and resourceful Senior Applied Scientist in the field of LLM, Artificial Intelligence (AI), Natural Language Processing (NLP), Recommender Systems and/or Information Retrieval, to invent and build scalable solutions for a state-of-the-art context-aware conversational AI. A successful candidate will have a strong machine learning background and a desire to push the envelope in one or more of the above areas.
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Contribute research to top-tier NLP conferences such as Association for Computational Linguistics (ACL) and Empirical Methods in Natural Language Processing (EMNLP) The Generative AI Systems (Genesis) team within Card Data Science builds state-of-art, generative AI-based solutions for dialogue, text summarization, reading comprehension, speech recognition, image/document processing as well as time-series sequencing modeling.
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Experience with natural language processing (NLP) and deep learning frameworks TensorFlow, PyTorch). Proficiency in programming languages such as Python, R, or SQL. Strong knowledge of machine learning techniques, statistical analysis, and data visualization tools Tableau, Power BI.
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Minimum of 5 years of technical experience and 3 years of experience specifically in data science and machine learning. Demonstrated expertise in machine learning, deep learning, and NLP, with a strong portfolio in large language models like GPT-3, BERT, and RAG.Advanced proficiency in Python, with hands-on experience in ML libraries and frameworks such as TensorFlow and PyTorch.
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Experience with analytic methods and technologies (artificial intelligence, machine learning/ deep learning/ neural networks, natural language processing, visualizations.
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Qualifications We DesireMaster’s degree in Computational Biology, Computational Bioengineering, Machine Learning, Statistics, Computer Science, Mathematics, or a related field. Knowledge and experience developing and applying algorithms in one or more of the following machine learning areas/tasks: deep learning, unsupervised feature learning, zero- or few-shot learning, active learning, transformer-based language modeling, multimodal learning, ensemble methods.
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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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Expertise in a subset of the following: machine learning, object detection, image segmentation, computer vision, image processing, remote sensing, spectral science, neural models for autonomous vehicles/robotics, structure from motion (SfM), natural language processing (NLP), large language models, data fusion, change detection, and pattern of life analysis.
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Helps team advance on plans for use of artificial intelligence, including Natural Language Processing, ChatGPT, predictive analytics, and leveraging machine learning to find hidden insights in data.
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In our Data science track we prepare you to get job as one of the following: Python developer, a data analyst, data visualization developer, a statistician, a machine learning engineer or a data scientist.
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machine learning natural language processing architectural design data science jobs Title: architect
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