Key Responsibilities:

• Design and implement NLP models for a range of tasks such as text classification, named entity recognition, sentiment analysis, and language generation.
• Develop and maintain scalable, production-level NLP pipelines and models.
• Collaborate with data scientists and engineers to integrate NLP models into larger AI systems.
• Work with large and unstructured datasets to preprocess and analyze text data.
• Experiment with state-of-the-art NLP techniques, such as transformers and deep learning models.
• Optimize NLP algorithms for performance and scalability in production environments.
• Perform data cleaning, feature engineering, and model tuning to improve accuracy and efficiency.
• Stay up-to-date with the latest advancements in NLP and AI research and apply them to real-world problems.
• Write clear, maintainable, and well-documented code.
• Communicate findings, insights, and solutions to both technical and non-technical stakeholders.

Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
• Proven experience in NLP, machine learning, and deep learning frameworks.
• Strong knowledge of NLP libraries such as SpaCy, NLTK, Hugging Face, or similar tools.
• Experience with machine learning frameworks like TensorFlow, PyTorch, or Keras.
• Familiarity with Python and data manipulation libraries (e.g., pandas, NumPy).
• Understanding of text processing techniques (tokenization, stemming, lemmatization).
• Experience working with large text corpora and data preprocessing pipelines.
• Strong problem-solving skills and the ability to think critically.
• Excellent communication and collaboration skills.
• Fluency in English (knowledge of Dutch is a plus).

Preferred Skills:

• Experience with transformer-based models like BERT, GPT, T5, etc.
• Familiarity with cloud-based services and deploying NLP models (AWS, Google Cloud, Azure).
• Experience in deploying and optimizing NLP models for production environments.
• Knowledge of data privacy and ethics in NLP.
• Contributions to open-source NLP projects or research papers in the field are a plus.

Salary and Benefits:

• Competitive salary depending on experience.
• Health insurance and pension contributions.
• Opportunities for professional development, training, and certification.
• Flexible working hours and the option for remote work.
• A collaborative and innovative work environment.
• Career growth opportunities in the AI and machine learning fields.