Natural Language Understanding Researcher

WE ARE LOOKING FOR Natural Language Understanding Researcher

We are seeking a highly skilled and innovative NLU Researcher to join our team. In this role, you will be at the forefront of pushing the boundaries of natural language understanding, developing cutting-edge techniques to enhance our products and services. You will collaborate with a talented team of researchers, engineers, and product managers to solve complex challenges and deliver impactful solutions.

Your future colleagues are waiting for you to join our international team. Working with us is uncomplicated, there’s a good team spirit, low-hierarchy and nonexistent bureaucracy. Our way of working is flexible too, many of our team work remotely from home with visits to our office from time to time when needed. This role is equally challenging, and as such we offer a very good compensation.

Main Responsibilities

Conduct advanced research in NLU, focusing on cutting-edge techniques for complex language understanding challenges, including content safety.

Design, implement, and optimize state-of-the-art NLU models.

Analyze large multilingual datasets to extract insights and improve model performance.

Experiment with different approaches to identify optimal solutions.

Collaborate with cross-functional teams to integrate NLU solutions.

Stay updated on the latest ML techniques and technologies.

Explore research opportunities and collaborate with academia.

Participate in defining content policy and research roadmaps.

Perform data analysis to inform decision-making and monitor model performance.

Evaluate new features and data sources to improve model capabilities.

Identify and track relevant metrics to measure model impact.

Communicate findings and recommendations effectively through visualizations and reports.

Required Qualifications

PhD in Computer Science, Linguistics, or a related field with a strong focus on natural language processing.

Proven experience in NLP and Computer Vision/Machine Learning.

Strong foundation in machine learning, deep learning, and natural language processing.

Proficiency in Python and experience with deep learning frameworks (e.g., TensorFlow, PyTorch).

Experience with multilingual text analysis, Transformers, knowledge representation, and knowledge graphs.

A strong track record of research and publications at top-tier conferences (e.g., ACL, EMNLP, NeurIPS, ICLR, ICML).

Knowledge of public cloud environments and technologies.