Research Science Intern

What you'll do

• Own a research project from initial problem framing to final write-up.
• Conduct experiments using large-scale compute and real-world data.
• Train machine learning models and manage GPU resources for experimentation.
• Read and reimplement recent research papers in relevant fields.
• Publish findings and incorporate the work into your doctoral dissertation.
• Translate fundamental research into practical systems for production use.
• Report honest empirical results, including failed ablations and unsuccessful experiments.

What we're looking for

• Must be currently enrolled in a PhD program at Carnegie Mellon University in machine learning, computer science, statistics, or a related field.
• Must have depth in at least one area relevant to the research goals of the lab.
• Must be comfortable running experiments, including training models, working with GPUs, and reimplementing recent papers.
• Must provide evidence of research ability through conference/workshop papers, preprints, open-source contributions, or a deep project.
• Must demonstrate "research taste" by explaining why a problem matters and the impact of its solution.
• Must practice honest empiricism by reporting experiments that did not work.
• Must have support from a faculty advisor.
• Export control regulations, some of these roles may require candidates to be eligible for any.