AIML Engineer Intern – Generative AI, PhD – Summer 2026 (Mountain View, CA)

This internship role will be based out of Mountain View CA. 

At LinkedIn our approach to flexible work is centered on trust and optimized for culture connection clarity and the evolving needs of our business. The work location of this role is hybrid meaning it will be performed both from home and from a LinkedIn office on select days as determined by the business needs of the team.

LinkedIn is seeking innovative and motivated PhD students to join our team as Generative AI Engineering Interns. As a part of our AI/ML teams you will work on advancing the frontier of Generative AI applying cutting-edge techniques in areas such as text generation image synthesis multimodal models evaluation frameworks and reinforcement learning. Youll collaborate with a dynamic group of AI researchers and engineers to develop scalable production-ready models that impact LinkedIns products and user experiences. LinkedIns 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 its 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 2026 or later.

Our internships are 12 weeks in length and will have the option of two intern sessions:

• May 26th 2026 - August 14th 2026
• June 15th 2026 - September 4th 2026 

Responsibilities:

• 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 LinkedIns platform
• Design and implement evaluation frameworks for AI models including metrics datasets and pipelines for automated testing and benchmarking
• Collaborate with product teams to build innovative AI-driven user experiences from personalized content to conversational agents
• Contribute to internal frameworks for human-in-the-loop annotation and preference modeling

Qualifications :

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
• Knowledge of generative models neural networks and probabilistic methods for AI
• Proven experience with programming languages such as Python and machine learning libraries like TensorFlow or PyTorch

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 prototyping 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)
• Proficiency in Python and deep learning frameworks (e.g. PyTorch TensorFlow JAX)
• 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 $62 to $75 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  Information :

Equal Opportunity Statement 

We seek candidates with a wide range of perspectives and backgrounds and we are 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.

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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 LinkedIns legal duty to furnish information.

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Pursuant to the San Francisco Fair Chance Ordinance LinkedIn will consider for employment qualified applicants with arrest and conviction records.

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No

Employment Type :

Full-time