Provide cloud software engineering support for a biometric facial recognition system
Shall have at least eight (8) years experi-ence in software development/engineering, including requirements analysis, software development, installation, integration, evaluation, enhancement, maintenance, testing, and problem diagnosis/resolution.
Shall have at least six (6) years of experience developing software with high level languages such as Java, C, C++.
Shall have experience with distributed scalable Big Data Store (NoSQL) such as Hbase, CloudBase/Acumulo, Big Table, and so forth.
Shall have experience with the Map Reduce programming model and technologies such as Hadoop, Hive, Pig, and so forth.
Shall have experience with the Hadoop Distributed File System (HDFS).
Shall have experience with serialization such as JSON and/or BSON.
Shall have at least three (3) years experience developing software for Windows (2000, 2003, XP, Vista), or UNIX/Linux (Redhat versions 3-5) operating systems.
Shall have experience on the design and development of at least one Object Oriented system.
Shall have experience developing solutions integrating and extending FOSS/COTS products.
Shall have at least three (3) years experience in software integration and software testing, to include developing and implementing test plans and test scripts.
Shall have demonstrated technical writing skills and shall have generated technical documents in support of a software development project.
Shall have demonstrated work experience in at least four (4) of the desired qualities below.
Experience deploying applications in a cloud environment.
Understanding of Cloud Scalability.
Hadoop /Cloud Certification.
Experience designing and developing automated analytic software, techniques, and algorithms.
Experience developing and deploying: analytics that include foreign language processing; analytic processes that incorporate/integrate multi-media technolo-gies, including speech, text, image and video exploitation; analytics that function on massive data sets, for example, more than a billion rows or larger than 10 Petabytes; analytics that employ semantic relationships (i.e., inference engines) between structured and unstructured data sets; analytics that identify latent patterns between elements of massive data sets, for example more than a billion rows or larger than 10 Petabytes; analytics that employ techniques commonly associated with Artificial Intelligence, for example genetic algorithms.
Experience with taxonomy construction for analytic disciplines, knowledge areas and skills.
Experience developing and deploying: data driven analytics; event driven analytics; sets of analytics orchestrated through rules engines.
Experience with linguistics (grammar, morphology, concepts).
Experience developing and deploying analytics that discover and exploit social networks.
Experience documenting ontologies, data models, schemas, formats, data element dictionaries, software application program interfaces and other technical specifications.
Experience developing and deploying analytics within a heterogeneous schema environment.