AIML - Machine Learning Researcher, MLR

Apple·Cambridge, Massachusetts, United States·posted 58m ago · last seen 1m ago

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About interviewing at Apple

One of tech's least standardized loops: you interview for a specific team, and every stage belongs to it. Recruiter/hiring-manager screen, one to three 45–60 minute Coderpad coding screens, a system design round shaped by Apple's reliability and privacy constraints, and a behavioral round — then a panel debrief. There is no central question bank; questions map to the team's real stack.

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Description

Summary

Play a part in building the next revolution of machine learning technology. We're looking for passionate mid-level and senior researchers to work on ambitious curiosity driven long-term research projects that will impact the future of Apple, and our products. In this role, you'll have the opportunity to work on innovative foundational research in machine learning. As a member of the team, you will be inspired by a diversity of challenging problems, collaborate with world-class machine learning engineers and researchers to impact the future of Apple products, and publish some of your results in high-quality scientific venues.

Description

In this position you will be responsible for pushing the boundaries of machine learning research. You will publish your results in top tier conferences and journal venues, making sure that your research results are reproducible and of high quality. You will collaborate with researchers to propose a research plan to advance our understanding of machine learning and execute it through implementation and experimentation, in collaboration with your colleagues. You will provide technical guidance, and prepare technical reports for publication and conference talks. You will have the opportunity to collaborate with broader teams across Apple.

Minimum Qualifications

Demonstrated expertise in machine learning research. Publication record in relevant conferences (e.g., NeurIPS, ICML, ICLR, AAAI, CVPR, ICCV, ECCV, ACL, EMNLP, etc). Hands-on experience working with deep learning toolkits such as PyTorch. Strong mathematical skills in linear algebra and statistics. PhD, or equivalent practical experience, in Computer Science, or related technical field.

Preferred Qualifications

Ability to formulate a research problem, design, experiment, implement and communicate solutions. Ability to work in a diverse collaborative environment.

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