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Experience with Lucene based open-source search tools like Solr or ElasticSearch. Founded in 2010, BrainTrust is an ever-growing and evolving company, with focus areas of Software Engineering (Machine Learning, Cloud Computing, HPC, Data Mining, HLT), Mission Operations (System Integration, Sensors, Deployment, Training, Support), and System Engineering (System Design, Requirements, Process Engineering, Resource Allocation.
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Strong experience with Linux Server platform Experience solving data engineering problems using technologies such as Spark, Solr. NoSQL database experience (MongoDB/Hadoop/Redis/DynamoDB/Elastic Search.
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Experience with open source textual processing such as Lucene, Sphinx, Nutch or Solr. Experience with entity extraction and conceptual search technologies such as LSI, LDA, etc. Involved in the analysis of unstructured and semi-structured data, including latent semantic indexing (LSI), entity identification and tagging, complex event processing (CEP), and the application of analysis algorithms on distributed, clustered, and cloud-based high-performance infrastructures.
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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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Experience with data access optimization for Cassandra, PostgreSQL and Solr/Elastic search and Lucene. We're seeking engineers with fresh ideas spanning information retrieval, distributed computing, large-scale system design, networking and data storage, artificial intelligence, and natural language processing.
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NET, XML, JSP, ASP.net, IIS, COBOL, 4GL, HTML or SharePoint, ATG, Documentum, Search Engines as SOLR, Autonomy, Oracle, SQL Server, etc. Provides complex database query skills such as SSIS, SRS, Stored Procedures or other complex queries to provide technical and business teams with requested data.
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This is a full-time position reporting to the Sr. Engineering Manager of our Search and Recommendation team. Excellent in analysis, modeling and problem-solving, and can see the essence of problems from complex data.
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Hands on experience with Text Mining and Text Search applications and frameworks like Elasticsearch or Solr or Lucene. 8+ years of experience in algorithms, machine learning, and natural language processing to build complex data driven software applications.
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Enterprise and Web Search concepts and Search Engines such as Apache Solr, LucidWorks Fusion, or Elastic Search; RDBMS like Oracle, MySQL or PostgreSQL, NoSQL DBs like MongoDB or Redis and data formats including XML and JSON.
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Knowledge of SOLR or another document-based search engine. Experience with Drupal backend development, particularly module development, content and data migration, and configuration management.
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Create efficient data messaging and access solutions for Kafka, Cassandra, and PostgreSQL databases. Proficiency in software programming with Java, Python, and Spark for data analysis and feature extraction.
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Experience with Enterprise Search Techologes (Solr, Elasticsearch, Lucene, or others) Experience with querying various databases (Oracle, SQL Server, MariaDB) using a variety of means (command line clients, desktop clients, code ) to analyze data and deduce missing or erroneous information.
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Nice to have experience with search engines like Apache Solr or similar. Strong knowledge and understanding of data structures, algorithms, design patterns, concurrency, multi-threading, scalability, fault tolerant designs, enterprise architecture and software engineering principles.
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DE customizing Hybris E-Commerce suite – Hybris Management console, Product Information Management, Content Catalog Management, Adaptive Search, Product Cockpit, Print Cockpit, Admin Console, Data Modeling, WCMS, Cronjobs, Impex scripts, and Workflow management according to business requirements.
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The Sponsor requires project management and technical support to manage projects and to perform software development activities within budget in the areas of enabling search against structured and unstructured data sets, coordinating and collaborating on documents across the organization, leveraging machine language to discover content that would otherwise be missed via Boolean, and incorporating artificial intelligence to do predictive analysis and make recommendations based on historical data.
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