Machine Learning (Explainable AI)

Overview

We are looking for a passionate and motivated researcher with a solid track record of solving challenging problems, advancing state-of-the-art, and demonstrated passion for ground-breaking research that could be scaled to production environment with an emphasis on the intersection of AI and Safety.

Responsibilities

• Create new techniques to make AI models more interpretable, unbiased, transparent and aligned with human values for real-world scenarios
• Create new techniques to ensure consistent alignment between user-centric explanations and intrinsic model behavior
• Reverse-engineer on neural networks to understand internal workings of AI models rather than treating them as black boxes
• Develop data attribution methods to quantify the influence of specific data points (text and image) on a model's prediction and implement solution
• Implement and integrate AI explainability techniques and tools