AIML Engineer Intern – Search and Recommender Systems, PhD – Summer 2026 (Mountain View, CA) at LinkedIn

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.Were looking for Artificial Intelligence Engineering interns to join our team and help shape the future of how LinkedIn connects members to opportunity. As an AI PhD intern youll work with massive semi-structured text graph and user activity data to design and build scalable intuitive recommender systems that power core LinkedIn experiences including the feed jobs and learning platforms.Youll collaborate with world-class engineers and researchers to create next-generation recommendation algorithms that improve personalization relevance and engagement across millions of users. Our Recommender Systems teams create personalization that enhances the user experience by showing relevant posts videos and connections keeping users engaged. We are looking for interns to help ensure that users are presented with fresh and relevant content encouraging them to keep coming back.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 2026June 15th 2026 - September 4th 2026Responsibilities:Conduct research and development on cutting-edge recommender systems applying techniques such as collaborative filtering matrix factorization deep learning and reinforcement learningDesign and implement scalable algorithms to personalize LinkedIns platform optimizing for relevance diversity and fairness in recommendationsCollaborate with engineering and product teams to integrate your solutions into LinkedIns ecosystem impacting millions of users globallyLeverage large-scale datasets to train and evaluate recommender models iterating on improvements to ensure optimal performanceWork in a highly collaborative environment with mentors business experts and technologists to conduct independent research and help deliver intuitive solutions to our products and services 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 internshipBackground in recommender systems machine learning or related areasProven experience with programming languages such as Python and machine learning libraries like TensorFlow or PyTorchKnowledge of key recommender system techniques including collaborative filtering content-based recommendations hybrid models and deep learning approachesExperience with evaluation metrics for recommendation quality (e.g. precision recall AUC diversity) Preferred Qualifications:Proficient in modern programming languages used in AI and large-scale systems including Python Java C and GoExperience with modern data processing frameworks such as Apache Spark Ray Flink or Databricks and familiarity with distributed computing paradigms (MapReduce cloud-native pipelines)Hands-on experience building and deploying recommender systems or large-scale ML models in production (e.g. leveraging embeddings graph neural networks or multi-task learning)Knowledge of Reinforcement Learning (RL) and Reinforcement Learning with Human Feedback (RLHF) techniques applied to recommendation or personalization tasksExperience with LLM-based or hybrid retrieval and ranking systemsProficiency with modern ML and deep learning frameworks  TensorFlow PyTorch JAX Hugging Face Transformers Scikit-Learn NumPy Pandas etc.Experience with cloud-based ML infrastructure (AWS Sagemaker GCP Vertex AI or Azure ML) and MLOps tools (MLflow Kubeflow Weights & Biases)Track record of research contributions or publications in top conferences such as NeurIPS ICML ICLR or KDDStrong communication and collaboration skills with the ability to translate complex technical concepts into business impactSuggested Skills:Experience or research in machine learning and deep learningExperience working with large data sets and data miningStrategic 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.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 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 youHaving interviews in an accessible locationBeing accompanied by a service dogHaving a sign language interpreter present for the interviewA 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.San Francisco Fair Chance Ordinance Pursuant to the San Francisco Fair Chance Ordinance LinkedIn will consider for employment qualified applicants with arrest and conviction records.Pay Transparency Policy Statement As a federal contractor LinkedIn follows the Pay Transparency and non-discrimination provisions described at this link: Data Privacy Notice for Job Candidates Please follow this link to access the document that provides transparency around the way in which LinkedIn handles personal data of employees and job applicants: Work : NoEmployment Type : Full-time Key Skills Microsoft Office,Public Relations,Google Docs,Data Collection,MailChimp,Microsoft Word,Dermal Fillers,Microsoft Powerpoint,Research Experience,Microsoft Excel,Adobe Photoshop,Writing Skills Department / Functional Area: Engineering Experience: years Vacancy: 1