Job Description
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.
We are looking for Artificial Intelligence interns to work on our massive semi-structured text, graph and user activity data sets. This internship will focus on various NLP or LLM concepts to help LinkedIn to become a more intuitive product. 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. This is a unique opportunity to apply your research expertise to real-world problems, collaborate with industry-leading AI/ML engineers, and build solutions that impact millions of users.
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,
recommendation solutions
• Research and develop innovative NLP models, with a focus on LLMs, to solve problems
related to information retrieval, text classification, machine translation, and question
answering.
• Design and implement scalable, production-level algorithms for natural language
understanding and generation.
• Collaborate with cross-functional teams to integrate NLP/LLM solutions into LinkedIn’s
platform, enhancing user experience and recommendation systems.
• Design Implement, train, and fine-tune LLM and GPT-like models on large-scale datasets to
ensure optimal performance and accuracy
- Select appropriate annotated datasets for Supervised Learning methods
- Use effective text representations to transform natural language into useful features
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
• Knowledge of core computer science concepts such as object-oriented design, algorithm
design, data structures, problem-solving, and complexity analysis
- Research experience in NLP, LLMs, or related areas.
- Experience in Python and popular deep learning frameworks such as TensorFlow, PyTorch, or
JAX.
• Experience working with transformer models (e.g., BERT, GPT, T5) and understanding of
attention mechanisms, transfer learning, and fine-tuning LLMs.
Preferred Qualifications:
- Experience with large-scale pretraining and fine-tuning of LLMs on diverse NLP tasks.
- Hands-on experience deploying NLP models in production environments.
- Experience with reinforcement learning, self-supervised learning, and few-shot learning in
NLP applications
• Practical knowledge with deep learning and machine learning algorithms and the use of
popular AI/ML frameworks
- Published work in academic conferences or industry circles
- Involvement in consumer-facing product development and design
- Experience with command of algorithms and data structures
- Understanding of text representation techniques (such as n-grams, bag of words, sentiment
analysis etc), statistics and classification algorithms
• Expertise in clustering, collaborative filtering, and classification techniques (Naïve Bayes,
SVM, NN, Boosting Methods, etc.)
• 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
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: Please reference and 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:
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This document provides transparency around the way in which LinkedIn handles personal data of employees and job applicants:
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