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Experience with data access optimization for Cassandra, PostgreSQL and Solr/Elastic search and Lucene. Experience with machine learning algorithms and tools, entity extraction, or natural language processing.
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Machine learning, artificial intelligence, neural networks experience is a huge plus (e.g. Tensorflow) Experience in distributed databases, NoSQL databases, full text-search engines (e.g. Elasticsearch, MongoDB, Solr.
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As aSr Software Machine Learning Engineer on the AI Search team,you will play a critical role inthe product’s AI architecture and roadmap. We’re looking for practical problem solvers with expertise in machine learning to enhance search, semantic search, Q&A, and search-assisted chat applications.
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Enlighten, honored as a Top Workplace from the Baltimore Sun, is a leader in big data solution development and deployment, with expertise in cloud-based services, software and systems engineering, cyber capabilities, and data science.
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Deep familiarity with one or more of the following areas at scale: Lucene-based search systems (ElasticSearch or Solr), search ranking and retrieval, data science, or information taxonomy.
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Working with both large and small-scale data sets to efficiently process information and design systems to use this data for machine learning purposes. Familiar with open source or commercial search technology such as Lucene, Solr, ElasticSearch, or Attivio.
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We're looking for software engineers that have experience in languages like Java, Ruby and Python and are interested in working in domains like big data analytics, search and discovery, and machine learning/NLP. In selecting projects, we look for challenging, mission-focused work where our teams can make a significant difference.
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Torin is looking for a qualified Data Scientist to develop algorithms, write scripts, build predictive analytics, use automation, apply machine learning and use the right combination of tools and frameworks to turn a set of data points into objective answers to help senior leadership make informed decisions.
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Coursework or thesis in machine learning, data mining, information retrieval, statistics or natural language processing. Experience in building large-scale machine-learning infrastructure for online recommendation, ads ranking, personalization, or search, etc.
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You will build zero-to-one machine learning capabilities, including learning-to-rank models for search result optimization, query and content understanding, personalization and machine learning based retrieval.
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Promoting advanced Coveo functionality (machine learning, Relevance and predictive analytics) and Coveo Cloud based search capabilities. Apache Solr, Elastic Search or any other enterprise search experience is added advantage.
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Experience creating and using machine learning algorithms and data structures. Your primary responsibility will be to develop groundbreaking machine learning applications, steering them from conceptualization to production within Reverb Search and Recommendations.
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Experience in application development using Java, Python, Spring Framework, SQL ServerExperience in web software development, including HTML5, JavaScript, and jQueryMinimum of 3 years experience in working in Search technologies: Solr, Elastic Search, LuceneExperience of AWS, auto scaling, Docker EE, and KubernetesExperience of gRPCExperience with Machine Learning Models for Application & Data related features is a plus.
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Familiarity with Information Retrieval/NLP/Data Mining/Machine Learning. Throughout 2019 we will replace four legacy Solr and Endeca search engines with your work. 2+ years experience dealing with search clusters - preferably Solr or Elastic-Search.
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Experience in streaming and/or batch analytics (e.g. Kafka, Spark, Flink, Storm, MapReduce, Hadoop) Experience with configuration management tools (e.g. Git, Nexus, Maven) 5+ years of experience in Software Engineering with an emphasis in cloud computing with a Bachelors in related field; 3 years relevant experience with Masters in related field; or High School Diploma or equivalent and 9 years relevant experience.
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