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Work Background
TEAM CANDI - Subsidiary of InfoQuest TechnologiesSoftware Engineer
Jun. 2024Athens, Attiki, Greece
ODIN Konsult ASBack-End Engineer
Jul. 2023 - Jun. 2024Oslo, NorwayArchitected and developed backend systems for various software solutions based on microservices.
Implemented data access layers, business logic, and API endpoints using Go, .NET, and ASP.NET Core.
Conducted code reviews, performed unit testing, and ensured code quality and adherence to coding standards.
Mentored junior engineers, provided technical guidance, and facilitated knowledge sharing sessions to foster a culture of learning and growth.
Valmore TechnologiesFull Stack Developer
May. 2023 - Nov. 2023Athens Metropolitan AreaSoftware solutions for a Smart Cities platform, incorporating userβs features using React.js .
Designed an administrative dashboard utilizing React.js to provide clients with a comprehensive overview of subscription costs of platform.
Orchestrated the backend development for both the dashboard and user platform using Node.js and MongoDB.
Greek ArmyPrivate
Jan. 2023 - Dec. 2023Athens, Attiki, GreeceIn my role within the Greek army, stationed at EFKA (Hellenic Organization of Social Security), I executed retirement procedures for officers. As a liaison between the military and EFKA, I ensured seamless coordination, compliance with regulations, and provided officers with comprehensive guidance on pension plans and benefits. Managing administrative aspects, including paperwork and financial institution coordination, I contributed to a smooth transition for Greek officers during their retirement journey.
GIXSOFTFull Stack Developer
Jun. 2022 - May. 2023Managing the complete software development process from conception to deployment about hospital workflow acceleration. Application based on React.js for client-side and Node.js as a server-side using MongoDB. Maintaining and upgrading the software following deployment using MERN Stack.
DeepLabMachine Learning Intern
Jun. 2022 - Oct. 2022Athens, Attiki, GreeceMachine learning models implementation using PyTorch for computer vision tasks as predicate detection, object detection using contrastive learning techniques. We selected CLIP OpenAI pretrained models utilized as backbones for feature extraction. We tested on a large scale for investigation of visual relationship classification performance in comparison with existing backbone of codebase. Also, we improved our text labels using Spacy for NLP engineering to summarize the impact of it into contrastive learning.
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