Machine Learning Engineer

Description

We currently have a vacancy for a Senior Machine Learning Engineer (AI/NLP) fluent in English, to offer his/her services as an expert who will be based in Belgium. The work will be carried out either in the company’s premises or on-site at customer premises. In the context of the first assignment, the successful candidate will be integrated with the Development team of the company that will closely cooperate with a major client’s IT team on site.

Your tasks

• Design, implement and optimise advanced AI, NLP, and ML models. Use LLMs, RAG frameworks, and other state-of-the-art approaches;
• Create methods for tokenisation, part-of-speech tagging, named entity recognition, classification, clustering and other text mining-related 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;
• Develop comprehensive reports and visualisations to communicate insights and findings to stakeholders.

Requirements

• University degree in IT combined with relevant IT professional experience of 17 years;
• Experience in Machine Learning and Natural Language Processing;
• Excellent knowledge of Python and libraries (e.g. Pandas, SpaCy, NLTK, Hugging Face);
• Experience with deep learning frameworks for complex model architecture such as TensorFlow or PyTorch;
• Experience with pre-trained models and LLMs like GPT, and other Transformer-based architectures;
• Experience with tools like Matplotlib and Seaborn for creating data visualizations;
• Experience with AI-powered code assistants (e.g., Amazon Q, Github Copilot), staying updated with advancements in AI-driven code technologies;
• Good knowledge of SQL tooling (Oracle, PostgreSQL);
• Knowledge of NoSQL databases (Elasticsearch, MongoDB);
• Knowledge of architectural design of scalable ML solutions such as model servers, GPU resource optimisation;
• Experience with A/B testing and experimental design of ML models;
• Strong understanding of linguistics and text processing techniques;
• Proficient in continuous code delivery and unit testing;
• Knowledge in one of the following areas: predictive (forecasting, recommendation), prescriptive (simulation), topic detection, plagiarism detection, trends/anomalies detection in datasets, recommendation systems;
• Familiarity with leveraging graph science techniques to solve complex data problems within social networks, knowledge graphs;
• Excellent command of the English language.