Research Scientist Intern, Muse Post-Training & Flywheel (PhD)

Responsibilities

Improve pipelines connecting product feedback, evaluation, training data, and Muse post-training. Build evaluations and curate training data to address product failures, including hallucinations. Run training experiments and work with researchers and engineers to improve model performance on real user tasks.

Qualifications

Currently pursuing a Ph.D. in Computer Science, Machine Learning, Natural Language Processing, or a related field Programming experience in Python and deep learning frameworks such as PyTorch Hands-on experience with model training, evaluation, or training data pipelines Must obtain work authorization in the country of employment at the time of hire and maintain ongoing work authorization during employment Experience with large language model post-training, reinforcement learning, or training data curation Intent to return to the degree program after completing the internship