Intern in Machine Learning Research (multi-modality | generative models | interpretability)

Summary

Posted: Oct 17, 2024
Weekly Hours: 35
Role Number:200574171

Play a part in the next revolution of machine learning research. Explore new methods, challenge existing metrics or protocols, develop new insightful theories that will change the way we understand machine learning. The Machine Learning Research team led by Samy Bengio, is looking for passionate PhD students to investigate the next generation of Machine Learning techniques with particular attention to multi-modality, generative models, interpretability, and alignment. As a member of the MLR team, you will work on some of the most challenging scientific questions, collaborate with world-class machine learning researchers, push forward innovative research agendas and publish ground-breaking research in international conferences.

Description

Are you passionate about advancing the state-of-the-art in ML and pursuing great innovation? As an intern in the Machine Learning Research team, you will receive technical mentorship and guidance from a dedicated senior researcher and will be able to collaborate with a dynamic, multidisciplinary and international team of researchers and engineers. Together with your mentor, you will decide on a line of research that will impact the scientific research community, future Apple products, and society. You will work towards a publication in a top machine learning venue towards the end of the internship and will be responsible for delivering ML research aligned with the core values of Apple, ensuring the highest standards of quality, scientific rigour, innovation, and respect for user privacy.

Minimum Qualifications

• A passion for multi-modal models, generative AI, interpretability, or alignment.
• Strong software engineering skills.
• Strong mathematical skills in linear algebra and statistics.

Preferred Qualifications

• * Demonstrated expertise in machine learning supported by a strong publication record in relevant conferences (e.g. NeurIPS, ICML, ICLR, AISTATS, CVPR, ICCV, ECCV, ICASSP, InterSpeech, AAAI, ACL, FAccT).
• * Hands-on experience working with Python and deep learning toolkits such as PyTorch and Jax.
• * Ability to formulate a research problem, design, experiment and implement solutions.
• * Ability to work in a collaborative environment.
• Applicants need to be pursuing a PhD in Machine Learning, Computer Science, Statistics, or a related technical field.