Research Scientist, Mechanistic Interpretability, Special Projects

Job description

Minimum qualifications: - PhD in Computer Science, a related field, or equivalent practical experience. - Experience building machine learning solutions, utilizing various machine learning architectures (e.g., deep learning, LSTMs, convolutional networks) and open-source frameworks (e.g., TensorFlow, PyTorch). - Experience in Python programming. - One or more scientific publication submissions for conferences, journals, or public repositories (e.g., CVPR, ICCV, NeurIPS, ICML, ICLR). Preferred qualifications: - 2 years of coding experience. - 1 year of experience managing and initiating research agendas. - Experience designing multi-modal, self-supervised pre-training tasks (e.g., contrastive learning, masked autoencoders) to improve data efficiency and manage sparse signals. About the job: As an organization, Google maintains a portfolio of research projects driven by fundamental research, new product innovation, product contribution and infrastructure goals, while providing individuals and teams the freedom to emphasize specific types of work. As a Research Scientist, you'll setup large-scale tests and deploy promising ideas quickly and broadly, managing deadlines and deliverables...