ML Research Scientist (probabilistic inference)

We are seeking a Machine Learning (ML) Research Scientist to join our team working on a novel AI safety research agenda. In this role, you will develop and evaluate probabilistic inference methods, with a focus on amortized inference, translating theoretical insights into practical implementations.

Key responsibilities

• Develop amortized inference methods suitable for high-dimensional discrete and continuous distributions.
• Develop parameter- and structure-learning methods for large probabilistic graphical models that benefit from amortized probabilistic inference.
• Design evaluation strategies for methods that rely on probabilistic inference.
• Collaborate with mathematicians on theory related to learning and inference in probabilistic models.
• Translate theoretical proposals into high quality implementations in a programming language such as Python.
• Analyze and interpret experimental results to steer future research directions.
• Communicate complex findings effectively to various stakeholders.
  

Skills and qualifications

• Advanced degree in a relevant field (e.g., Computer Science, Mathematics). A PhD is preferred but not required if the candida