About the role

AI & Data Engineer designing and deploying AI solutions for EU-funded research projects at Telelink Business Services. Collaborative role requiring hands-on model development and cross-functional teamwork in an international environment.

Responsibilities

Design, implement, and evaluate machine learning and AI models for research-driven and applied innovation use cases
Preprocess, clean, and analyze structured and unstructured data to support model development and data driven experimentation in EU projects
Integrate AI models into applications or services (as an example via APIs or microservices), ensuring compatibility with project architectures and partner systems
Collaborate with cross-functional teams (researchers, developers, domain experts) in international EU-funded consortia, supporting technical coordination and alignment
Prepare technical documentation, reports, and contributions to EU project outputs, in line with the funding requirements
Participate in experiments, benchmarking, and performance optimization of AI models
Monitor model performance in production and propose improvements
Stay up to date with current AI/ML tools, frameworks, and best practices, and actively contribute to internal knowledge sharing and innovation activities
Support the preparation of project proposals, technical annexes, and concept notes in collaboration with project managers and researchers
Contribute to the alignment of AI solutions with data protection, ethics, and EU regulatory frameworks

Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or related field (or equivalent practical experience)
1–3 years of experience working with AI/ML or data-focused software development (internships and academic projects count)
Solid programming skills in Python and experience with AI/ML libraries (as an example PyTorch, Transformers, TensorFlow, or scikit-learn) and LLM frameworks (as an example LangChain, LlamaIndex, or LangGraph)
Understanding of core machine learning concepts (supervised and unsupervised learning, model evaluation, overfitting, etc.)
Familiarity with deep learning (as an example neural networks, transformers, computer vision, or NLP models)
Experience with data processing tools, vector databases, or RAG (Retrieval-Augmented Generation) pipelines
Basic understanding of MLOps concepts (version control, reproducible experiments, environments, CI/CD, or model deployment)
Fluent English (C1 level or equivalent) with the ability to write clear technical documentation and communicate with international stakeholders in EU-funded projects
Ability to work in multidisciplinary and international project teams, following structured project workflows and timelines
Required to pass a security background check for access to classified information

Impact: Be part of a dynamic and collaborative environment where you can have a significant impact in the ever-evolving field of IT technologies
Innovation: Be part of a team that thrives on staying ahead of the curve in the ever-evolving field of technologies
Collaboration: Create and drive a community around you
Professional growth: Continuous Learning and Career Upskilling Opportunities
Flexibility and Hybrid working model
Performance-based Bonus Scheme