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I applied for the Software Development Engineer Intern position at LinkedIn through the off-campus hiring process. The process was mainly focused on Data Structures and Algorithms, and the coding rounds were quite strict about time and space complexity. Round 1 — Online Coding Assessment The first round was an online coding assessment. There were 4 coding questions to be solved in 90 minutes. The questions were based on standard data structures and algorithms, but the time limit made it important to move quickly between problems. The assessment was the first elimination round, and candidates who performed well were shortlisted for the technical interview. I managed to clear the online assessment and moved to the next stage. A separate LinkedIn India SDE Intern report also describes a four-question coding assessment as the first stage of the off-campus process. Round 2 — Technical Interview The technical interview lasted around an hour and consisted of two DSA problems. The first problem was based on finding the first and last position of an element in a sorted array. The interviewer specifically wanted an optimized O(log N) solution. I initially discussed the straightforward approach, but the interviewer made it clear that simply scanning the array would not be sufficient. The key was to use binary search twice — once to find the first occurrence and once to find the last occurrence. I explained the binary-search approach and discussed the complexity before moving towards implementation. The second problem was based on reversing the words in a string. The interviewer again placed constraints on the solution. The expected solution needed to run in O(N) time and O(1) extra space. I explained the approach and worked through the edge cases involving spaces and the ordering of the words. The interview was not just about getting the correct output. The interviewer paid close attention to whether the solution met the required complexity. The public candidate report specifically notes that only the optimized complexities were accepted for both questions. After the technical round, I expected to proceed to the next stage, but I was eventually informed that I had not been selected for the HR round. Result Unfortunately, I was not selected after the technical round. The experience was still useful because it showed me how important optimization is in interviews at companies like LinkedIn. Knowing the basic solution to a problem isn't always enough. If the interviewer gives a specific complexity requirement, the solution has to satisfy it. The first problem was a good example of this. A linear search could find the required positions, but because the array was sorted, the expected solution had to take advantage of that property and use binary search. The second problem similarly tested whether I could think about both time and space complexity instead of focusing only on getting the correct output. Preparation Takeaways After the interview, I realized that my preparation needed to focus more on optimized DSA solutions rather than simply solving a large number of problems. For a similar LinkedIn SDE internship process, I would focus on: Arrays and strings Binary search Two pointers Hashing Stacks and queues Trees and graphs Recursion Dynamic programming Time and space complexity I would also practice explaining the solution before coding. In an interview, it is important to make the reasoning clear rather than immediately jumping into implementation. Another LinkedIn SDE internship report from India describes a longer process involving an online test, technical interview and two host-manager interviews, with the candidate eventually rejected despite solving the technical questions. This shows that the exact process can vary between LinkedIn hiring drives. Overall, this was a good learning experience. The questions themselves were based on familiar DSA concepts, but the strict complexity requirements made the interview more challenging than a standard coding round. The main lesson for me was to always think about whether my solution is not only correct, but also optimal for the given constraints.