Summary

Application Deadline: Sunday 23rd November Play a part in the revolution of machine learning research. Explore innovative methods, challenge existing metrics and protocols, develop new informative theories that reshape our understanding of ML. The Machine Learning Research team led by Samy Bengio, is looking for hard-working researchers to investigate the next generation of ML techniques, with a focus on multi-modality, generative models, interpretability, and alignment. As a member of the team, you will solve some of the most challenging scientific questions, collaborate with world-class machine learning researchers, drive innovative research agendas and publish ground-breaking research at international conferences.

Description

Are you passionate about advancing the state-of-the-art in machine learning and driving meaningful innovation?As an intern in our team, you will receive technical mentorship and guidance from a dedicated researcher and 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 at large. Your work will be geared towards a publication at a top machine learning venue by the end of the internship. You will deliver high-quality ML research aligned with Apple's core value, ensuring the highest standards of quality, scientific rigour, innovation, and respect for user privacy. We are looking for individuals with a background in machine learning research, as shown through academic publications or equivalent experience. Ideal candidates will have a deep curiosity for working at the intersection of foundation models and interactive reinforcement learning agents.

Minimum Qualifications

Pursuing a PhD in Machine Learning, Computer Science, Statistics, or a related technical field.
Confirmed 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.

Preferred Qualifications

Strong software engineering skills.
A passion for one of the following areas: multi-modal models, generative AI, reinforcement learning and agentic systems.
Strong mathematical skills in linear algebra, statistics and analysis.
Ability to work in a collaborative environment

Machine Learning Research Internship

Artificial Intelligence, Machine Learning Research

Apple

Summary

Description

Minimum Qualifications

Preferred Qualifications