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The company is focused on some very cool machine learning technologies melded with mobile and location-based applications. About the JobI’m working with one of the Co-Founders of a 12 person startup with solid funding that started in 2015 out of MIT. The team is located in Boston and are looking for a talented backend software engineer to work on building and scaling their platform for real-time optimization and data analysis using Java8 / Scala and Python.
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Our consultants bring deep expertise in Data Science, Machine Learning and AI. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner.
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Our diverse workforce includes skilled tradespeople; artificial intelligence, machine learning (AI/ML) experts; engineers; technologists; scientists; logistics experts; and business administration professionals.
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Our capabilities range from C5ISR, AI and Big Data, cyber operations and synthetic training environments to fleet sustainment, environmental remediation and the largest family of unmanned underwater vehicles in every class.
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Develop Azure Databricks data engineering, AI, and machine learning tasks. In this role, the Data Warehouse Developer (Remote) will be responsible for for successful design, development, and delivery of Azure Databricks Lakehouse solutions within a SQL Server Data Warehouse environment.
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Employs mathematics, statics, information science, artificial intelligence, machine learning, network science, probability modeling, data mining, data engineering, data warehousing, data compression, data protection, and / or other scientific techniques to correlate complex, technical findings into graphical, written, visual and verbal narrative products on trends of existing intelligence data to leverage other IC data sources.
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Experience with virtualization technologies like VMware or Hyper-V. Knowledge and some experience in AI areas like machine learning, AI engineering, Data engineering/scientist is in plus.
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We specialize in Computer Network Operations (CNO), embedded development, software engineering, cloud engineering, Artificial Intelligence and Machine Learning (AI/ML), DevOps support, systems engineering and more.
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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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Develops and utilizes machine learning and data mining algorithms, including, but not limited to, Multiple Information Model Synthesis Architecture (MIMOSA) prediction algorithms based on open-source capabilities.
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Enterprise Big Data Solution provides FIS big Data capabilities including large scale data processing, analytics, fraud platforms, machine learning engineering, stream processing and data insights.
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Azure experience is preferred, both traditional cloud resources and ETL/ELT tools such as Azure Data Factory, Databricks, Machine Learning Workspace, Container Apps, App Services, API Management, Application Gateway, and Front Door.
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Configure and maintain on-premises High Performance Computing (HPC) infrastructure in close collaboration with computational chemistry and machine learning teams. A mindset for continuous learning, strong communication and problem-solving skills will be required for effective cross-functional collaboration with Automation, Computational Data Science and Scientific teams, including Platform Chemistry, Medicinal Chemistry, and pre-clinical Biology.
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Experience as a Mongo Data Administrator, with a blend of database experience with MongoDB, SQL Server, and Cassandra. Experience with statistical analysis, machine learning, predictive modeling, and/or optimization.
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Job Title Big data Administrator Relevant Experience (in Yrs) Min 3-5 yrs Must Have Technical/Functional Skills " Proficiency in the Cloudera suite, including Kafka, HDFS, HBASE, KUDU, Zookeeper, HIVE, Impala, NIFI, SPARK, FLINK, Oozie, Yarn, Atlas, Ranger, RangerKMS, and KTS. " Experience with Cloudera ECS and Cloudera Data Services such as Cloudera Data Engineering, Cloudera Data Warehouse, and Cloudera Machine Learning.
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