First round 30 minute call over the phone. Brief resume screening and then dived right into probability questions. The interview did give some hints - but was not really useful.

The interview process for the Machine Learning Intern role at Tower Research Capital typically begins with an online assessment, often hosted on HackerRank. This test usually includes a combination of algorithmic coding problems, mathematical puzzles, and sometimes questions on probability, statistics, or machine learning fundamentals. Candidates are advised to attempt it only when they have uninterrupted time, as it allows a single login session and monitors for plagiarism. Those who perform well are shortlisted for one or more technical interviews. These interviews often focus on data structures, algorithmic thinking, machine learning concepts, and coding skills in Python or C++. Additionally, candidates may be evaluated on their understanding of probability, linear algebra, and optimization — all key to quantitative trading. In some cases, a final round may include system design or a discussion about previous ML projects, followed by a culture-fit or HR interview. Overall, the process is rigorous, aiming to assess both theoretical knowledge and practical problem-solving ability in a high-pressure setting.