苹果Computer Vision/Machine Learning Engineer (Low level CV)
任职要求
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: Low level object detection and segmentation / ML-based ISP / Multi-sensory fusion / Multi-modal fusion in ISP • 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 …
工作职责
The computer vision algorithm engineer 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: Machine learning based ISP; Low level object detection and segmentation; Multiple sensor fusion
The computer vision algorithm engineer 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.
NVIDIA is now looking for an Intern of System Software Engineers for its Autonomous Vehicle teams. As an intern of our team, you will be responsible for assisting senior engineers on developing and maintaining software to drive the car, given various sensor input devices including Camera’s, LIDAR, RADAR, GPS, IMU and others on Vehicle CAN, work with different teams here to transform the information into driving the car with the best experience. You will work with different teams on all sort of challenging problems for autonomous driving including computer vision, deep learning, object tracking, car controlling. You will help build the software and make it work flawlessly and safely on our driving platform. We expect you to have strong communication, organizational, and analytical skills. Solid understanding and strong system software experience is a requirement. Experience with GPU technology, image processing, computer vision, and multimedia are highly valued. Familiarity with deep learning / artificial intelligence is desirable. What you’ll be doing: • Craft the driving application for Autonomous Vehicle products • Solve the real challenging problems in the software with different teams and to drive the car with the best experience • Performance optimization on our driving platforms
The computer vision algorithm engineer 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.
As a Machine Learning Engineer, you will be entrusted with the critical role of innovating and applying state-of-the-art research in foundation models to tackle complex problems. The solutions you develop will significantly impact future Apple products and the broader ML development ecosystem. You will work with a multidisciplinary team to actively participate in the data-model co-design and co-development practice. Your responsibilities will extend to the design and development of data processing pipeline, modeling methodology and effective evaluation metrics. Furthermore, you will have the opportunity to showcase your groundbreaking research work by publishing and presenting at premier academic venues.