Machine Learning Engineer Intern (Privacy and Data Protection Office) - 2026 Start (PhD)

Responsibilities: Lead and collaborate with cross-functional teams to design, develop, and deploy advanced machine learning algorithms to enhance privacy-related systems. Formulate end-to-end ML models leveraging NLP techniques to process signals from privacy products and incidents. Analyze large and complex datasets to extract meaningful insights, identify opportunities for improvement, and drive data-driven decision-making. Design and execute experiments to test and iterate on models, aiming to optimize recommendation functions and user satisfaction. Communicate final recommendations to stakeholders and influence decisions. Build analytics tools and platforms to measure privacy evolution, validate findings, and tell compelling data stories. Collaborate with engineering, legal, audit, security, public policy, government relations, and product teams to develop deep domain knowledge in privacy.

Qualifications: Minimum: Master’s or PhD in Computer Science, Mathematics, Statistics, Operations Research or related field; strong NLP and analytics background; experience with Python and SQL; experience with data extraction, cleaning, and presentation for medium to large datasets; familiarity with NumPy, SciPy, Pandas, Scikit-learn; hands-on experience with ML/DL methods. Preferred: experience with forecasting, time series, hypothesis testing, classification, clustering or regression; data visualization; ML libraries such as PyTorch, TensorFlow, Keras; experience with Large Language Models is a plus.