AI/NLP Engineer
Uni Systems
full-time
Posted on:
Location Type: Hybrid
Location: Brussels • Belgium
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About the role
- 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.
- Fine-tune pre-trained models on 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 visualisations to communicate insights and findings to stakeholders.
Requirements
- Master + 11 years of relevant experience
- 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 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.
- 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.
- 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 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.
- Proficiency in understanding and applying statistical concepts and models.
- Ability to formulate problems and develop solutions using data-driven approaches.
- Good communication skills in English, both orally and in written form.
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
AINLPMLPythonPandasSpaCyNLTKTensorFlowPyTorchSQL
Soft skills
communicationcollaborationproblem-solvinganalytical thinkingcreativityattention to detailadaptabilityresearchpeer reviewcontinuous improvement
Certifications
Master's degree