Foundation Models Intern: ML Research & Fine-Tuning

New Grad; San Francisco (CA); On-site; USD 34,000 - 55,000; Part time

Job summary

42dot is seeking an intern to help our team develop and evaluate foundation models. You’ll work alongside machine learning engineers, gain experience with model training and fine-tuning, and own a focused project with clear deliverables.

As part of our internship, you’ll reproduce baseline results, explore improvements, run experiments, and contribute reusable code and docs. You’ll present findings to the team and grow in a hands-on, collaborative environment.

Qualifications

• Strong Python programming skills and familiarity with PyTorch or a similar framework.
• Understanding of machine learning fundamentals, deep learning, and transformer architectures.
• Experience with an ML project through coursework, research, or personal work.
• Ability to debug problems, interpret experimental results, and communicate clearly.
• Curiosity, initiative, and willingness to learn.

Responsibilities

• Reproduce baseline results and understand our models, datasets, and evaluation workflows.
• Implement and evaluate improvements in fine-tuning, data quality, or inference efficiency.
• Run controlled experiments and analyze model performance, computational cost, and failure cases.
• Contribute reusable code, evaluation tools, and technical documentation.
• Present your findings and recommendations to the team.

Skills

Python

PyTorch

Deep learning

ML fundamentals

Debugging

Education

Coursework in ML

Tools

Git

Jupyter

Job description

42dot is seeking an intern to help our team develop and evaluate foundation models. You’ll work alongside machine learning engineers, gain experience with model training and fine-tuning, and own a focused project with clear deliverables.

As part of our internship, you’ll reproduce baseline results, explore improvements, run experiments, and contribute reusable code and docs. You’ll present findings to the team and grow in a hands-on, collaborative environment.