Computer Vision and Machine Learning Intern

Summary

Be a part of the Video Computer Vision (VCV) group at Apple and join the team behind object tracking on visionOS. We’re looking for candidates with a strong background in 3D Computer Vision, Machine Learning and ideally Computer Graphics.

Description

You will join a team of computer vision and machine learning researchers and engineers to discover and build solutions to previously-unsolved challenges and push the state of the art. As a member of a fast-paced team, you have the unique and rewarding opportunity to shape upcoming products that will delight and inspire millions of people every day.

Minimum Qualifications

• Currently has or is in the process of obtaining a masters or PhD degree in Computer Science, Computer Vision, Machine Learning or relevant technical field
• Thourough knowledge of machine learning fundamentals, with hands-on familiarity in PyTorch and writing ML training loops
• Solid software engineering skills in complex, multi-language systems. Fluency in Python
• Excellent communication and collaboration skills

Preferred Qualifications

• A track record of publishing academic research in top-tier peer-reviewed venues
• Expertise in projective 3D geometry and 6 DoF pose estimation
• Experience in working on computer graphics pipelines (implementing shaders, mesh processing, etc.)
• Software development experience with C++
• Strong overall software development approach. You deliver clean, well-tested code

At Apple, we're not all the same. And that's our greatest strength. We draw on the differences in who we are, what we've experienced, and how we think. Because to create products that serve everyone, we believe in including everyone. Therefore, we are committed to treating all applicants fairly and equally. We will work with applicants to make any reasonable accommodations.

At Apple, we believe accessibility is a fundamental human right. You’ll find that idea reflected in everything here — in our culture, our benefits and our digital tools. By welcoming as many perspectives as possible, we help you build a career where you feel like you belong.

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Role Number: 200655115-1731