Karkidi
Machine Learning Engineer Intern, Computer Vision Algorithm (Video Understanding
Karkidi, Cupertino, California, United States, 95014
The computer vision algorithm intern will work in a dynamic team as part of the Video Computer Vision 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.
All potential candidates should read through the following details of this job with care before making an application.Minimum QualificationsDuring the internship, you must be enrolled in a M.S. or PhD program 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: Video Understanding / Video Foundation Model / Multi-modal LLM.Proven prototyping skills and proficient in coding (C, C++, Python).Excellent written and verbal communication skills, be comfortable presenting research to large audiences, and have the ability to work hands-on in multi-functional teams.Preferred QualificationsPublication record in relevant venues (e.g., NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, SIGGRAPH).Industry experiences with multi-modal foundation models and frameworks.Knowledge and understanding of generative AI, multi-modal large language models, and video captioning.Solid understanding of the state-of-the-art in Video Understanding and familiarity with the challenges of developing algorithms that run efficiently on resource-constrained platforms.Team-oriented, result-oriented, and self-motivated.
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All potential candidates should read through the following details of this job with care before making an application.Minimum QualificationsDuring the internship, you must be enrolled in a M.S. or PhD program 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: Video Understanding / Video Foundation Model / Multi-modal LLM.Proven prototyping skills and proficient in coding (C, C++, Python).Excellent written and verbal communication skills, be comfortable presenting research to large audiences, and have the ability to work hands-on in multi-functional teams.Preferred QualificationsPublication record in relevant venues (e.g., NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, SIGGRAPH).Industry experiences with multi-modal foundation models and frameworks.Knowledge and understanding of generative AI, multi-modal large language models, and video captioning.Solid understanding of the state-of-the-art in Video Understanding and familiarity with the challenges of developing algorithms that run efficiently on resource-constrained platforms.Team-oriented, result-oriented, and self-motivated.
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