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Extended AI
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Developed an web application which can manage to interpret different Machine Learning experiments and give accuracy results based on the given data.
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Created a job manager using a messaging queue (Google Pub/Sub) for the interaction between the core application and the Machine Learning component.
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Used different Google Cloud tools such as Google Storage or different SQL instances for data storage.
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Used GraphQL (query language) as an alternative to classic REST API, for a better handling of objects for the front-end component.
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Contributed in all phases of Software Development Life Cycle based on Agile methodology, including bug fixing and problem investigation.
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Participated in code review.
Technologies: Java 11, Spring Boot, Hibernate, Maven, PostgreSQL, Google GCP, Google Pub/Sub, GraphQL.
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Data governance application
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Worked on an data ingestion application composed of multiple Java application modules, each having a different functionality in the context of file transfer(FTP, SFTP, HDFS).
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Implemented various features consisting of storing different reports as metadata in Apache Atlas and Elasticsearch.
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Interacted closely with the Big Data department which had the major role in creating pipelines with Apache Airflow using the Java modules.
Technologies: Java 8, Spring Boot, Hibernate, Maven, PostgreSQL, Elasticsearch.
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Automotive application
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Worked on a complex web application developed for a big automotive company. The application stores millions on labeled data about issues found on cars that can be grouped, cataloged and filtered.
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Worked in an Agile format, interacting with product owners within the Scrum process.
Technologies: Java 8, Spring Boot, Hibernate, Maven, OracleDB, Apache Solr.
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RESTful Web Server in Spring
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Developed an application for extracting specific data from candidates' CV using Machine Learning algorithms in order to provide a score which would assist the recruiter in choosing the best candidate for a job.
Technologies: Spring Boot, Kafka, Livy, HBase.