Job Details

Role Number: 200617451-0836

Summary

Play a part in building the next revolution in machine learning technology. We’re looking for passionate researchers to work on ambitious, curiosity-driven, long-term research projects. 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

You have a strong research background in machine learning or related fields and regularly publish your work in leading conferences and journals. You are committed to producing high-quality, reproducible research. In this role, you will have the opportunity to define and drive a research agenda at the intersection of machine learning and graphics, with a focus on generative modeling for 3D/4D content, video, audio, and simulation. You will advance our understanding of these areas through rigorous experimentation and close collaboration with colleagues. You will also develop high-quality code, provide technical mentorship, and prepare publications and presentations for top-tier venues. Additionally, you will have opportunities to collaborate with broader teams across Apple.

Minimum Qualifications

• Demonstrated expertise in machine learning and generative modeling research

• Publication record in relevant conferences (e.g., NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, SIGGRAPH, etc.)

• Strong hands-on experience working with Python and deep learning toolkits such as PyTorch

• Experience with C++, CUDA, and graphics or rendering simulation environments is a strong plus

• Strong mathematical skills in linear algebra and statistics

Preferred Qualifications

• Ability to formulate a research problem and design, experiment, implement, and communicate solutions.

• Ability to work in a diverse, collaborative environment.

• High-quality open-source contributions to related projects.

• PhD or equivalent practical experience in Computer Science or a related technical field.

• Strong presentation skills for internal and external communications.