Expert in AI/NLP/ML -
QY95WRY5
Location: Remote, Brussels Budget300 - 345euro/day
1. CONTEXT/INTRODUCTION
European Commission agency which covers areas of substantial societal and political significance, and ensures the strategic implementation of EU flagship programmes including Erasmus+, the European Solidarity Corps, Creative Europe, the Marie Skłodowska-Curie Actions and the European Institute of Technology (EIT).
2.DESCRIPTION OF THE TASKS
Key tasks:
Design and Development:
o Architect, design, and implement advanced machine learning models, including but not limited to
deep learning, reinforcement learning, and large language models (LLMs).
o Develop scalable AI solutions using state-of-the-art techniques and frameworks.
o Collaborate with data scientists to refine data preprocessing, feature engineering, and model training
pipelines.
Deployment and Integration:
o Deploy machine learning models and AI solutions into production environments, ensuring scalability,
performance, and reliability.
o Integrate AI models with existing systems and workflows, providing seamless functionality across
platforms.
o Optimize models for performance, including latency, throughput, and accuracy, considering both cloud and edge deployment scenarios.
Research and Innovation:
o Stay up-to-date with the latest advancements in AI, ML, and LLM technologies, and apply them to
enhance our AI capabilities.
o Experiment with new algorithms, architectures, and techniques to push the boundaries of AI within
the organization.
o Contribute to research publications, patents, and open-source projects as appropriate.
Collaboration and Communication:
o Work closely with cross-functional teams to understand business requirements and translate them into
technical solutions.
o Communicate complex AI concepts and technical details to non-technical stakeholders effectively.
o Mentor junior engineers and provide guidance on best practices in AI and ML development.
Testing and Evaluation:
o Conduct rigorous testing and validation of AI models, including A/B testing, cross- validation, and
error analysis.
o Monitor model performance in production and iterate on models to improve accuracy and robustness.
o Implement monitoring systems to detect model drift and ensure continued performance over time.
3.LEVEL OF EDUCATION - Master/Bachelors Degree
4.KNOWLEDGE AND SKILLS
Following skills and knowledge are required for the performance of the above listed tasks:
o Proven experience in designing, implementing, and deploying advanced machine learning models and
AI systems.
o Strong experience with large language models (LLMs) and natural language processing (NLP)
techniques.
o Experience with cloud platforms (AWS, Azure).
Technical Skills:
o Deep understanding of machine learning frameworks and libraries.
o Experience with data processing and ETL tools. o Familiarity with MLOps practices and tools.
Soft Skills:
o Strong problem-solving skills and the ability to think critically and creatively.
o Excellent communication skills, both written and verbal.
o Ability to work collaboratively in a team environment and independently with minimal supervision.
Non-technical skills:
Capability of integration in an international/multicultural environment, rapid self- starting capability and experience in working in team;
Ability to work in multi-cultural environment, on multiple large projects;
Excellent Team Player
Ability to understand, speak and write
High degree of discretion and integrity is required
English (B2)