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We apply advanced technologies such as Digital Signal Processing, Analytics, Machine Learning, Artificial Intelligence, and Cloud computing to solve our customer and mission challenges. Explore new machine learning and artificial intelligence approaches for automated object detection, feature extraction/target state estimation, multi-source data fusion, and much more.
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Knowledge of software and algorithm development, machine-learning algorithm development, or artificial intelligence techniques applied to digital RF signal processing, RF engineering or spectrum theory, communication systems, electronic warfare, SIGINT processing, or related areas.
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Experience leveraging Esri's software capabilities including, mapping, field operations, spatial analysis and data science, 3D visualization and analytics, data management, and developer APIs.
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Experience with cognitive computing, data integration, data mining, Natural Language Processing, Hadoop platforms, or automating machine learning components. This is a chance to use your deep OS knowledge and broaden your skill set into areas like Cloud computing, large-scale data ingestion and processing, multiple data store types, including graph data, time series, spatial, and other NoSQL, high performance data streaming, data science, and supporting the integration of novel mission applications and analytics.
$81,800 - $186,000 a yearFull-timeExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
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Deep expertise in one or more data science specialties, such as natural language processing, computer vision, or deep learning. + Develop models and solutions for problem sets in a broad range of data science areas, including but not limited to natural language processing, graph analytics, computer vision, anomaly detection, data visualization, and metrics creation.
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Job Description: Parsons is seeking motivated individuals dedicated to solving a full spectrum of signal processing challenges in Herndon, VA for SIGINT, EW, Radar, and Communications Systems.
$68,400 - $119,700 a yearExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
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Certifications and specialization in IT Ops, Infrastructure, APM, Data Engineering, Machine Learning, Data Infrastructure. Master data modeling, develop and optimize queries, tune and scale clusters, prioritizing fast search and analytics at scale.
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Geospatial tools, Big Data and Graph Products (Hadoop, MapReduce, Spark, ElasticSearch, Neo4j), Linux, OpenStack, AWS, Ansible, SQL/NoSQL, Text Processing, Cloud Services, Containerization, Infrastructure as Code (IAC), and more.
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A master’s or PHD degree in electrical engineering - Proficiency in hardware description languages (Verilog, VHDL) and FPGA development tools (Xilinx Vivado, Intel Quartus, etc. We are seeking a qualified candidate for the role of FPGA Engineer who will be responsible for designing, implementing, and testing FPGbased solutions for critical signal processing applications.
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Data Science, Software Engineering, Cloud/AWS Infrastructure, and Cyber/CNO are our core areas of expertise. We are a multi-faceted software development and systems administration team working to build and maintain software applications backed by a self-managed cloud infrastructure (OpenStack) with a true big-data footprint (over 10 petabytes.
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Strong engineering experience with the following core platforms and services:VMware ESXi and vSphereMicrosoft Windows Server and Deployment and AdministrationMicrosoft Windows 10 Deployment and Administration DNS, DFS, and DHCPActive Directory and defining, implementing, and maintaining Group Policy Microsoft SCCM with Operating System Deployment (OSD)Data center networking fundamentals (experience with software defined data center networks a plus.
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Much of our work contributes to innovative research in the fields of sensor science, signal processing, data fusion, artificial intelligence (AI), machine learning (ML), and augmented reality (AR.
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Demonstrated proficiency in the design and implementation of modern data architectures and concepts such as cloud services (e.g., AWS, Azure, GCP), real-time data distribution (e.g., Kafka, Kinesis,DataFlow, Airflow), NoSQL (e.g., MongoDB, DynamoDB, HBase, CosmosDB) and modern data warehouse tools including Snowflake and DataBricks.
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Responsible for data engineering source code control using GitLab. Basic Qualifications:Experience with relational databases and knowledge of query tools and/or BI tools like Power BI or OBIEE and data analysis tools.
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Minimum of 8 years of hands-on experience as a data quality engineer, imagery analyst, GIS analyst, or quality assurance engineer in the space of satellites, computer vision, or machine learning.
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