R&D Intern - Fairness in Deep Learning

About the role

This research internship focuses on developing methods to ensure neural network predictions remain independent of continuous sensitive variables such as age or income. The intern will explore bias reduction techniques, implement existing regularization methods, and design new approaches to mitigate discrimination in machine learning models. The role is based at the Artefact research center in Paris.

Responsibilities

• Implement existing bias reduction methods based on dependency measures
• Establish a robust protocol to compare different fairness methods
• Analyze the trade-off between model performance and fairness
• Design and experiment with new bias reduction methods for continuous variables
• Maintain reproducible code using open source libraries

Required skills

• Machine Learning
• Deep Learning
• Mathematics
• Statistics
• PyTorch
• scikit-learn

Qualifications

• Master's degree in Applied Mathematics, Statistics, or Machine Learning
• Currently enrolled in a university or engineering school

About the Company

Artefact is an international data services company specializing in data transformation consulting. With 2500 employees, the firm bridges the gap between data and business to deliver tangible results through AI technologies and agile methods.