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

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