AI/ NLP/ ML expert at COSMOTE GLOBAL SOLUTIONS NV

Brussels, Brussels-Capital, Belgium -

Full Time

Start Date

Immediate

Expiry Date

12 Mar, 26

Salary

0.0

Posted On

12 Dec, 25

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

AI Solutions Development, Natural Language Processing, Machine Learning, Generative AI, Python, Data Management, Cloud Computing, DevOps Practices, Data Pipelines, Metadata Management, MLOps, Data Visualization, Ethical AI, Project Management, Quality Assurance, Big Data Analytics, Corpus-Based Linguistics

Industry

IT Services and IT Consulting

Description

COSMOTE Global Solutions, as a member of OTE Group of Companies, is an ICT Systems Integrator delivering a broad range of ICT Solutions and Services. CGS provides a broad range of ICT Services focusing on: Cloud, Data Centre operations, Networking, Cybersecurity, BI and Data Warehouse, Big Data, Service Desk, Proactive Monitoring, Operations and Support, Service Management, Project and Programme Management, and Professional Services. Responsibilities: Development and maintenance of AI solutions, defined as software applications that integrate AI (Natural Language Processing, Machine Learning, Generative AI). Design and implement of IT architecture for AI solutions under expert understanding of most appropriate AI components, techniques and models, applying modern AI approaches, as well as modern IT architecture practices. Present AI solutions blueprints to technical and business audiences. Moderate discussions and collect relevant technical and business feedback. Support implementation of best practices for data, master- and metadata management and modern MLOps. Training of custom machine learning and deep learning models (including transformer-based architectures) based on structured and unstructured data. Master’s Degree on a related field 10+ years of experience in IT Excellent knowledge of Python and its core AI/ML/NLP libraries and frameworks (e.g., pandas, OpenAI, spaCy, PyTorch, TensorFlow, Transformers, scikit-learn, NLTK). Proven experience with advanced AI/ML techniques including large language models, generative AI architectures, RAG, agentic workflows (OpenAI, LangChain, CrewAI), function calling, MCP, and traditional machine learning algorithms in production environments. Strong experience with modern data management and engineering techniques, including data pipelines, metadata/model versioning, and database integration (relational SQL and NoSQL solutions like Elasticsearch, MongoDB, Cassandra). Strong experience with cloud computing platforms (AWS, Azure) for deploying, scaling, and securing AI solutions. Practical knowledge of modern software engineering and DevOps practices including Git workflows, CI/CD pipelines, containerization (Docker, Kubernetes), and agile methodologies. Demonstrated ability to independently develop, test, document, and integrate AI/ML components as part of larger service-oriented architectures. Experience with ethical/legal implications of AI systems in enterprise or public sector environments is highly desirable. Experience with MS Teams, Intellij, Jira, Enterprise Architect Experience with Project Management Methodologies such as Agile and PM² Excellent knowledge of Data Management Good knowledge of Linux. Good knowledge of Unix and Bash. Good knowledge of natural language processing systems lifecycle and agile software development methodologies. Good knowledge of quality assurance and quality control for machine translation (MT) and experience with MT quality procedures, testing methodologies and tools, such as automatic quality metrics (BLEU scores and similar) and human evaluation of MT quality. Knowledge of query languages, such as SQL, Hive, Pig, and with information extraction Knowledge of NoSQL databases, such as MongoDB, Cassandra, HBase, etc. Knowledge of data visualization tools, such as D3.js, GGplot. Experience in the field of corpus-based linguistics. Experience with alignment models and classification methods. Experience with data analytics over big datasets, nonstructured databases as well as data lakes. Optional certifications: AWS Certified Machine Learning Microsoft Azure AI Engineer Associate SAS Certified Professional AI and Machine Learning Certification.

Responsibilities

The role involves the development and maintenance of AI solutions, including software applications that integrate AI technologies. Additionally, the expert will design IT architecture for AI solutions and present blueprints to both technical and business audiences.