AI/NLP/ML Expert Job Description

Start Date: 01/03/2026

Duration: Initial contract for 180 days, with potential extension

Location: Belgium

Language Requirement: English

Responsibilities:

• Design, implement, and optimize advanced AI, NLP, and ML models.
• Utilize LLMs, RAG frameworks, and other state-of-the-art approaches.
• Develop methods for tokenization, part-of-speech tagging, named entity recognition, classification, clustering, and other text mining-related tasks.
• Fine-tune pre-trained models for domain-specific tasks.
• Conduct thorough research and stay updated on the latest trends and advancements in NLP, ML, and AI technologies.
• Develop and maintain robust, scalable, and efficient code using Python.
• Collaborate with cross-functional teams to integrate AI/ML solutions into existing products and services.
• Perform rigorous analysis and experimentation to improve model accuracy, efficiency, and scalability.
• Participate in peer reviews and contribute to the continuous improvement of AI solutions.
• Contribute to the design and implementation of ML application architecture and its solution stack.
• Develop comprehensive reports and visualizations to communicate insights and findings to stakeholders.

Required Qualifications and Experience:

• Expert level (Level 6-8) in AI/NLP/ML.
• Experience in Machine Learning and Natural Language Processing.
• Excellent knowledge of Python and libraries such as Pandas, SpaCy, NLTK, and Hugging Face.
• Experience with deep learning frameworks like TensorFlow or PyTorch.
• Familiarity with AI-powered code assistants (e.g., Amazon Q, GitHub Copilot).
• Good knowledge of SQL tooling (Oracle, PostgreSQL) and NoSQL databases (Elasticsearch, MongoDB).
• Knowledge of architectural design for scalable ML solutions, including model servers and GPU resource optimization.
• Experience with A/B testing and experimental design of ML models.
• Proficiency with pre-trained models and LLMs like GPT and other Transformer-based architectures.
• Experience with data visualization tools like Matplotlib and Seaborn.
• Strong understanding of linguistics and text processing techniques.
• Proficient in continuous code delivery and unit testing.
• Understanding of bias in ML applications and bias mitigation techniques.
• Knowledge in areas such as predictive (forecasting, recommendation), prescriptive (simulation), topic detection, plagiarism detection, trends/anomalies detection in datasets, and recommendation systems.
• Proficiency in understanding and applying statistical concepts and models.
• Ability to formulate problems and develop solutions using data-driven approaches.
• Effective communication of complex data insights to non-technical stakeholders.
• Results-oriented mindset with a focus on delivery.
• Good communication skills in English, both orally and in written form.
• Ability to write clear and well-structured documentation.