Research Scientist Graduate - Seed Model, Vision

About the team The Seed Vision team focuses on foundational models for visual generation, developing multimodal generative models, and carrying out leading research and application development to solve fundamental computer vision challenges in GenAI. We are looking for talented individuals to join our team. As a graduate, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth. Successful candidates must be able to commit to an onboarding date by the end of the year. Please state your availability and graduation date clearly in your resume. Candidates can apply to a maximum of two positions and will be considered for jobs in the order you apply. The application limit is applicable to our Company and its affiliates' jobs globally. Applications will be reviewed on a rolling basis - we encourage you to apply early. Responsibilities - Develop and scale vision foundation models across image and video modalities. - Design data pipelines, pre-training strategies, and post-training methods for vision tasks. - Improve core capabilities such as perception, reasoning, and multimodal understanding. - Optimize model architectures, training efficiency, and evaluation frameworks. - Explore real-world applications of vision models in multimodal systems. Minimum Qualifications: - Individuals who are completing or have recently completed a BS degree in Computer Science, Electrical Engineering, Electrical and Computer Engineering, Physics, Mathematics, or a related discipline. - Excellent coding ability, data structures, and fundamental algorithm skills, proficient in C/C++ or Python, etc. - Demonstrated interest or project experience in relevant areas. Preferred Qualifications: - Individuals who are completing or have recently completed a MS degree in Computer Science, Electrical Engineering, Electrical and Computer Engineering, Physics, Mathematics, or a related discipline. - Experience with computer vision, multimodal learning, or machine learning through internships is preferred. - Strong problem-solving and communication skills.