Μονάδα Υποστήριξης Φοιτητών (Μ.Υ.Φ.)

Επισυνάπτονται 7 διαφορετικές αγγελίες για θέσεις οι οποίες άνοιξαν πρόσφατα και αφορούν entry level & junior level υποψηφίους.

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We are looking for an experienced and passionate WordPress Developer to join our ΙΤ team in our satellite office in Patras (Greece). The role is for a person to be responsible for both back-end and front-end development, including understanding of aesthetics (understanding element arrangements on the screen, the color and font choices, and so on).

We are expecting the correct candidate to have a strong understanding of latest industry trends and content management systems.

Responsibilities:

-Designing and implementing new features and functionality

Επισυνάπτεται η θέση εργασίας.

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We are looking for a passionate Full-stack Software Engineer, with excellent programming skills, to design, and work on the development of the PerCV.ai platform. In this role, you should be able to work with an agile team of experienced programmers. The candidate should have excellent organizational, problem-solving skills and mainly willingness to learn new technologies.

We are looking for a passionate DevOps/MLOPs Engineer, with good understanding of the DevOps principles applied to code and/or data and Machine Learning (ML) models, to design, and work on streamlining processes related to code, data and ML models. The candidate should have excellent organizational, problem-solving skills and mainly willingness to learn new technologies.

Responsibilities:

We are looking for a Business Development Representative / Account Executive to help us meet our customer acquisition and revenue growth targets by keeping Irida Labs competitive and innovative. You will be responsible for maximizing our marketing and sales team potential, crafting sales plans, and making sure that our customers have a positive experience.

Responsibilities:

We are looking for a passionate, research focused Machine Learning Engineer, with practical and/or theoretical knowledge in any of the following areas: computer vision, machine/deep learning, statistical and reinforcement learning. Skills on embedded programming will be acknowledged, to explore the most efficient and practical implementations of these algorithms in embedded platforms.

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