LinkedIn was built to help professionals achieve more in their careers, and everyday millions of people use our products to make connections, discover opportunities, and gain insights. Our global reach means we get to make a direct impact on the world’s workforce in ways no other company can. We’re much more than a digital resume – we transform lives through innovative products and technology. LinkedIn is seeking innovative and motivated PhD students focused on Video Processing and Generative AI. You will develop state-of-the-art video processing models and generative AI solutions to enhance video recommendations, content creation, and user interactions. This role will allow you to leverage cutting-edge deep learning techniques in video understanding, synthesis, and generation, shaping the future of video-driven experiences on LinkedIn. Our mission is crystal clear: to elevate the LinkedIn member experience through the implementation of cutting-edge technologies that enable advanced cognitive understanding of multimedia content. Whether it's text, images, videos, ads, or live content, we are leading the way in developing state-of-the-art large vision language technologies. •Candidates must be currently enrolled in a PhD program, with an expected graduation date of December 2025 or later. At LinkedIn, we trust each other to do our best work where it works best for us and our teams. This role offers a hybrid work option, meaning you can both work from home and commute to a LinkedIn office, depending on what’s best for you and when it is important for your team to be together. Our internship roles will be based in Mountain View, CA; or other US office locations. Our internships are 12 weeks in length and will have the option of two intern sessions: • May 27th, 2025 - August 15th, 2025 • June 16th, 2025 - September 5th, 2025 Responsibilities: •Work with large data sets, crunching millions of samples for statistical modeling/data mining for large-scale model training. •Conduct research and development on video processing techniques, including video classification, object detection, action recognition, and video summarization. •Explore and apply generative AI models (e.g., GANs, VAEs, diffusion models) to video synthesis, video-to-video translation, and content creation, enhancing personalized user experiences. •Develop deep learning models for video-based recommendation systems and personalized content generation, focusing on video quality, relevance, and user engagement. •Collaborate with cross-functional teams to integrate generative AI video models into LinkedIn’s platform, optimizing for performance and scalability. •Collaborate with Machine Learning Engineers and other stakeholders to deliver impact on LinkedIn’s newsfeed or other products Basic Qualifications: •PhD student in Computer Science, Machine Learning, or related fields, with a focus on video processing, computer vision, or generative AI, and expected graduation in 2025 or later. •Background in video processing, deep learning, and generative models, particularly GANs, VAEs, or diffusion models. •Experience with Python and deep learning frameworks (e.g., PyTorch, TensorFlow). •Experience working with video datasets and architectures such as 3D CNNs, optical flow, and spatio-temporal models. Preferred Qualifications: •Experience applying generative AI techniques to video tasks, such as video synthesis, inpainting, super-resolution, or video style transfer. •Experience with large-scale video processing and generation in real-world applications, particularly in recommendation systems or user-generated content platforms. •Knowledge of video compression, enhancement, and streaming technologies. • Publication record in video processing, computer vision, or generative AI conferences (e.g., CVPR, ICCV, ECCV, NeurIPS). •Hands-on experience deploying generative video models in production environments. •Proven proficiency with command of algorithms and data structures •Excellent communication skills Suggested Skills: • Machine Learning and Deep Learning • Advanced Data Mining • Strategic thinking and problem-solving capabilities LinkedIn is committed to fair and equitable compensation practices. The pay range for this role is $57 - $70 per hour. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to skill set, depth of experience, certifications, and specific work location. This may be different in other locations due to differences in the cost of labor. The total compensation package for this position may also include annual performance bonus, stock, benefits and/or other applicable incentive compensation plans. For more information, visit https://careers.linkedin.com/benefits. Equal Opportunity Statement LinkedIn is committed to diversity in its workforce and is proud to be an equal opportunity employer. LinkedIn considers qualified applicants without regard to race, color, religion, creed, gender, national origin, age, disability, veteran status, marital status, pregnancy, sex, gender expression or identity, sexual orientation, citizenship, or any other legally protected class. LinkedIn is an Affirmative Action and Equal Opportunity Employer as described in our equal opportunity statement here: https://microsoft.sharepoint.com/:b:/t/LinkedInGCI/EeE8sk7CTIdFmEp9ONzFOTEBM62TPrWLMHs4J1C\_QxVTbg?e=5hfhpE. Please reference https://www.eeoc.gov/sites/default/files/2023-06/22-088\_EEOC\_KnowYourRights6.12ScreenRdr.pdf and https://www.dol.gov/ofccp/regs/compliance/posters/pdf/OFCCP\_EEO\_Supplement\_Final\_JRF\_QA\_508c.pdf for more information. LinkedIn is committed to offering an inclusive and accessible experience for all job seekers, including individuals with disabilities. Our goal is to foster an inclusive and accessible workplace where everyone has the opportunity to be successful. If you need a reasonable accommodation to search for a job opening, apply for a position, or participate in the interview process, connect with us at accommodations@linkedin.com and describe the specific accommodation requested for a disability-related limitation. Reasonable accommodations are modifications or adjustments to the application or hiring process that would enable you to fully participate in that process. Examples of reasonable accommodations include but are not limited to: -Documents in alternate formats or read aloud to you -Having interviews in an accessible location -Being accompanied by a service dog -Having a sign language interpreter present for the interview A request for an accommodation will be responded to within three business days. However, non-disability related requests, such as following up on an application, will not receive a response. LinkedIn will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. 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