Linkedin

I applied for the LinkedIn Software Engineer Intern position through the off-campus process. The initial screening was mainly based on my application and resume, after which I received the coding assessment. I knew LinkedIn could have some fairly difficult DSA questions, so I spent most of my preparation time revising trees, heaps, dynamic programming and common interview patterns. The coding assessment had multiple DSA problems under a fixed time limit. I did not find all of them equally difficult, so I first secured the questions where I immediately recognized the pattern. Once I had enough confidence in those solutions, I returned to the harder problem and worked through the constraints carefully. Reports from LinkedIn candidates show that the OA format can vary, with some candidates receiving three questions in 90 minutes and others reporting four coding questions. After clearing the assessment, I had the technical interview. The interviewer started with a short introduction and then moved directly into coding. The first problem was based on a Binary Search Tree. I was asked to reason about the tree rather than simply implement a standard traversal, so I first clarified the expected behavior and then discussed the recursive solution. The second question was considerably more interesting. It involved a priority queue and required me to think about how the data structure could efficiently maintain the required elements while operations were being performed. I initially considered sorting repeatedly, but after looking at the constraints I realized that would be unnecessarily expensive. I explained the heap-based approach, implemented it, and then walked through the complexity. The interviewer also asked several follow-ups. Instead of stopping once the main solution worked, I had to explain what would happen with duplicate values, empty input and larger constraints. I was comfortable with those discussions because I had already made it a habit to test my solutions against edge cases during practice. A recent selected LinkedIn intern report similarly describes a technical interview involving a BST problem followed by a priority-queue problem, with the latter being around medium-to-hard difficulty. The next conversation was much less code-heavy. I spoke with a manager about my projects and technical background. One question that stood out was asking about the first moment that made me interested in software engineering. We also discussed one of my projects in more depth, including what I personally implemented and the technical decisions I made. I made sure not to describe the project only at a high level. Whenever I mentioned a technology, I was prepared to explain why I used it and what alternative I had considered. After the final discussion, I received the selection confirmation. The process taught me that LinkedIn's internship interviews can move quickly from a standard DSA problem into deeper follow-ups, so knowing the pattern alone is not enough. I needed to understand why the solution worked and be ready to modify it when the interviewer changed the requirements.