As Research Software Engineers (RSEs) for the Princeton Language and Intelligence Initiative, we work on research projects that are challenging from both a scientific and engineering standpoint. We share many core responsibilities with traditional researchers, in particular conducting experiments, publishing papers, and pushing knowledge boundaries - with a special focus on computational methods and software systems. Partnering up with graduate students, postdocs, and faculty, we turn research ideas or proofs of concepts into projects that work reliably, scale and reach the state of the art. Additionally, we collaborate with scientists who are exploring concepts in machine learning theory, addressing challenges such as reproducibility and the rigorous understanding of theoretical frameworks.

Our roles range from providing technical and machine learning advice, to project-specific software development, or spearheading research directions that leverage our computational and machine learning expertise.