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I applied for the Software Engineer Intern role at LinkedIn through the off-campus hiring process. After the initial application and screening, I received an online coding assessment. The process was fairly DSA-focused from the beginning, and the interview stage continued in the same direction. The first stage was the online coding round. I was given two DSA problems of moderate difficulty. The questions required me to identify the right approach rather than simply implementing a standard algorithm. I focused on solving the problems efficiently and making sure the complexity was within the expected limits. The assessment was time-bound, so managing time between the two questions was also important. I was able to complete the coding round and move ahead in the process. The next stage was the technical interview. The interview started with a short introduction. After that, the interviewer moved directly into DSA. The problems were more challenging than the questions I had seen in the online assessment. One of the problems involved a tree. I had to think about the structure of the tree and work towards an efficient traversal-based solution. The interviewer was interested in my reasoning, so I explained the brute-force idea first and then discussed how the solution could be optimized. The discussion then moved to another DSA problem involving finding the majority element. Instead of stopping at one solution, I was asked to discuss different possible approaches and their complexities. I explained the straightforward approach using frequency counting and then discussed how the problem could be solved more efficiently without maintaining a frequency map. We discussed the reasoning behind the optimized approach and the conditions under which it works. The interview was not just about getting the final answer. I was expected to explain my thought process while solving the problem, discuss edge cases, and justify the time and space complexity. There were also questions around general problem-solving ability. The interviewer wanted to see how I approached a problem that I had not immediately seen before. I tried to break the problem down into smaller parts and communicate my ideas before writing the final code. The technical round was the most challenging part of the process. The DSA questions required me to think beyond the basic implementation and consider more optimized solutions. Unfortunately, I was not selected after the interview. Looking back, the process was a useful experience because it showed me that LinkedIn's internship interviews can be heavily focused on algorithmic problem solving. The questions were not necessarily about obscure concepts, but they required strong fundamentals and the ability to move from a basic solution to an optimized one. For preparation, I would focus on arrays, hashing, trees, graphs, recursion, searching and optimization techniques. It is also important to practice explaining your solution while solving because the interviewer is evaluating the reasoning process as well as the final code. One of my main takeaways from the interview was that knowing a problem pattern is only part of the preparation. I also needed to become faster at identifying the underlying pattern when the problem was presented in a slightly different form. Overall, I couldn't convert the LinkedIn interview into an internship, but the experience gave me good exposure to the type of DSA questions expected in a product-company SWE internship interview.