JP Morgan Chase ML Engineer role

I interviewed for a Senior Associate Machine Learning position at JP Morgan Chase. With over 7 years of experience primarily in AI/ML, focusing on NLP, OCR, AWS Sagemaker, Azure Machine Learning, and some basic computer vision, I was eager for this role. The interview process itself was a bit challenging to schedule, with the call being rescheduled 5-6 times before it finally took place. When the 45-minute call began, the interviewer joined about 5 minutes late. Approximately 10-15 minutes into the session, a coding question was presented. The interviewer directly shared a LeetCode link to the problem "Subarray Sum Equals K." I struggled with the problem; initially, I failed to consider zero values, which I then fixed. I received a hint from the interviewer to use a hash map, but unfortunately, I then made a mistake by considering an O(n) array memory solution. Afterward, I failed to account for negative values. By the time I was attempting to fix these issues, the allocated time for the problem was over. The interview did not cover any topics related to AI/ML, NLP, GenAI, RAG, or Multi-agents, focusing instead on Python DS & Algo. I was subsequently rejected.