Computer Vision/Machine Learning Intern

5 days ago

Beijing, Beijing, China Apple Full time
If you are the kind of people who are passionate on pursuing excellence, embracing challenges, enjoying work with others, learning new things along the way, Apple is the right place for you.

The ideal candidate will possess the self-motivation, curiosity, and initiative to achieve those goals. Analogously, the candidate is a lifelong learner who passionately seeks to improve themselves and the quality of their work.

Description
The computer vision algorithm intern will work in a dynamic team as part of the Video Engineering org which develops on-device computer vision and machine perception technologies across Apple's products. We balance research and product to deliver the highest quality, state-of-the-art experiences, innovating through the full stack, and partnering with cross-functional teams to influence what brings our vision to life and into customers hands.

Keywords: Object detection and segmentation; Multiple sensor fusion; Activity Recognition; Video Caption

Minimum Qualifications
M.S. or PhD in Electrical Engineering/Computer Science or a related field (mathematics, physics or computer engineering), with a focus on computer vision and/or machine learning

Rich experiences in video machine learning covering one of the topics: Object detection and segmentation; Multiple sensor fusion; Activity Recognition; Video Caption

Proven prototyping skills and proficient in coding (C, C++, Python)

Excellent written and verbal communications skills, be comfortable presenting research to large audiences, and have the ability to work hands-on in multi-functional teams

Preferred Qualifications
Publication record in relevant venues (e.g. NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, SIGGRAPH)

Industry experiences with multi-modal foundation model and frameworks

Knowledge and understanding of generative AI, multi-modal large language model, video caption

Solid understanding of state-of-the-arts in Video Understanding and familiar with the challenges of developing algorithms that run efficiently on resource constrained platforms

Team oriented, result oriented, and self motivated

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