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From creating experiments and prototyping implementations to designing new architectures, our research scientists work on real-world problems that span the breadth of computer science, such as machine (and deep) learning, data mining, natural language processing, hardware and software performance analysis, improving compilers for mobile platforms, as well as core search and much more.
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End-to-end hands-on experience with building data processing pipelines, large scale machine learning systems, and big data technologies (e.g., Hadoop/Spark) 4+ years of industry experience applying machine learning methods (e.g., user modeling, personalization, recommender systems, search, ranking, natural language processing, reinforcement learning, and graph representation learning.
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As a Research Scientist, you'll setup large-scale tests and deploy promising ideas quickly and broadly, managing deadlines and deliverables while applying the latest theories to develop new and improved products, processes, or technologies.
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We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day.
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Define the data structure, framework, design, and evaluation metrics for research solution development and implementation under minimal guidance. Responsibilities Author research papers to share and generate impact of research results across the team and in the research community.
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7+ year Experience in Search, Machine Learning, NLP, Large Language Models and applying these techniques at scale. In-depth knowledge of machine learning algorithms and ability to apply them in data driven natural language processing systems.
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Experience in a wide variety of projects utilizing natural language processing, artificial intelligence, data compression, machine learning and search technologies. Theoretical and practical experience with modern machine learning algorithms and tools, including deep learning and NLP.
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An advanced degree (Undergrad, M.S. or equivalent experience) in Operations Research, Statistics, Applied Mathematics, Data Science or related field or 10 + years of proven experience crafting optimization and machine learning solutions for large scale applications.
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Establish scalable, efficient, automated processes for large-scale data mining, machine-learning model development, model validation and serving. - Technical leadership in large-scale machine learning, deep learning, and large language models for recommendation systems.
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Working knowledge in one or more of the following: machine learning (ML), data mining, information retrieval, search or statistics. LinkedIn's Machine Learning Engineers are both data/research scientists and software engineers, who develop and implement machine learning models and algorithms.
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Deliver on large portions of a project by defining the data structure, framework, design, and evaluation metrics for research solution development and implementation. Author research papers to share and generate impact of research results across organization and in the research community.
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Key word search: Python, Master's degree, predictive maintenance, preventative maintenance, relocation package, data science. Develop internal APM product utilizing the latest anomaly detection machine-learning algorithms for predicting machine failures.
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Experience with large scale distributed systems, data processing pipelines and machine learning training and serving infrastructure. Prior experience building machine learning systems in production such as enabling data analytics at scale.
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Search for ways to automate and scale time series data solutions across the business. Working knowledge of machine learning application (eg. - Perform exploratory data analysis in search of new data solutions.
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Experienced in at least one area of the following areas: personalized recommendations, search engine, machine learning, distributed storage system, big data frameworks is a plus.
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