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 to join our team as Generative AI Engineering Interns. As a part of the AI/ML team, you will work on advancing the frontier of Generative AI, applying cutting-edge techniques in areas such as text generation, image synthesis, multimodal models, and reinforcement learning. You’ll collaborate with a dynamic group of AI researchers and engineers to develop scalable, production-ready models that impact LinkedIn’s products and user experiences. LinkedIn's Machine Learning Engineers are both data/research scientists and software engineers, who develop and implement machine learning models and algorithms. Unlike other companies that separate these roles, our engineers work on projects from ideation to implementation.
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.
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.
Candidates must be currently enrolled in a PhD program, with an expected graduation date of December 2025 or later.
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 BIG data, crunching millions of samples for statistical modeling, data mining, recommendation solutions
• Conduct research and development on state-of-the-art Generative AI models, including transformers, diffusion models, GANs, and autoregressive architectures.
• Apply advanced Generative AI techniques to a variety of tasks such as text generation, creative content generation, conversational agents, and multimodal learning.
• Develop and implement large-scale, production-quality Generative AI systems that integrate with LinkedIn’s platform.
• Collaborate with product teams to build innovative AI-driven user experiences, from personalized content to conversational agents.
• Keep up-to-date with emerging trends in Generative AI, contributing to research communities through publications in leading AI conferences and journals.
• Collaborate with Machine Learning Engineers and other stakeholders to deliver impact on LinkedIn’s newsfeed or other products
Basic Qualifications:
• Currently pursuing a PhD in computer science, statistics, mathematics, electrical engineering, machine learning, or related technical field and returning to the program after the completion of the internship
• Proven research experience in Generative AI, including LLMs, GANs, VAEs, diffusion models, or similar architectures.
• Experience in Python and deep learning frameworks (e.g., PyTorch, TensorFlow, JAX)..
• Knowledge of generative models, neural networks, and probabilistic methods for AI.
• Experience with transformer architectures, autoregressive models, and training techniques for generative tasks.
Preferred Qualifications:
• Proven track record in developing machine learning algorithms for solving computer vision and graphics problems (e.g., generative models for images and videos), as well as prototype invented algorithms.
• Experience with multimodal learning, combining visual and textual data in Generative AI systems.
• Knowledge of reinforcement learning applied to Generative AI tasks.
• Hands-on experience deploying generative models in production environments.
• Publication record in AI/ML conferences (e.g., NeurIPS, ICML, CVPR, ICCV).
• Involvement in consumer-facing product development and design
• Understanding of configuration management techniques and tools
• 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. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by LinkedIn, or (c) consistent with LinkedIn's legal duty to furnish information.
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As a federal contractor, LinkedIn follows the Pay Transparency and non-discrimination provisions described at this link: https://lnkd.in/paytransparency.
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This document provides transparency around the way in which LinkedIn handles personal data of employees and job applicants: https://lnkd.in/GlobalDataPrivacyNotice
