The posting
Meta is seeking PhD interns with strong machine learning and programming skills to improve Muse through applied product projects. Interns will work on the post-training flywheel, turning product feedback into measurable model improvements.
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.
Minimum 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
Preferred Qualifications
- Experience with large language model post-training, reinforcement learning, or training data curation
- Intent to return to the degree program after completing the internship



