Senior Machine Learning Engineer (AI/NLP)

Talent Quanta is seeking 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.

Key Responsibilities

• Design, implement and optimise advanced AI, NLP, and MLmodels. 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 textmining-related tasks;
• Conduct thorough research and stay updated on the latesttrends and advancements in NLP, ML, and AI technologies;
• Develop and maintain robust, scalable, and efficient codeusing Python;
• Collaborate with cross-functional teams to integrate AI/MLsolutions into existing products and services;
• Perform rigorous analysis and experimentation to improvemodel accuracy, efficiency, and scalability;
• Develop comprehensive reports and visualisations tocommunicate insights and findings to stakeholders.

Required Expertise

• University degree in IT combined with relevant ITprofessional experience of 17 years;
• Experience in Machine Learning and Natural LanguageProcessing;
• Excellent knowledge of Python and libraries (e.g. Pandas,SpaCy, NLTK, Hugging Face);
• Experience with deep learning frameworks for complex modelarchitecture such as TensorFlow or PyTorch;
• Experience with pre-trained models and LLMs like GPT, andother Transformer-based architectures;
• Experience with tools like Matplotlib and Seaborn forcreating data visualizations;
• Experience with AI-powered code assistants (e.g., Amazon Q,Github Copilot), staying updated with advancements in AI-driven codetechnologies;
• Good knowledge of SQL tooling (Oracle, PostgreSQL);
• Knowledge of NoSQL databases (Elasticsearch, MongoDB);
• Knowledge of architectural design of scalable ML solutionssuch as model servers, GPU resource optimisation;
• Experience with A/B testing and experimental design of MLmodels;
• Strong understanding of linguistics and text processingtechniques;
• 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, recommendationsystems;
• Familiarity with leveraging graph science techniques tosolve complex data problems within social networks, knowledge graphs;
• Excellent command of the English language.