The interview process began with an initial technical screening centered around algorithmic problem-solving and my experience handling unstructured data pipelines. This was followed by a technical deep-dive where I was asked to walk through the system architecture of my machine learning workflows, specifically detailing how I benchmarked and tuned my models. The final round felt unstructured and shifted away from core engineering competencies, focusing heavily on domain-specific financial compliance and regulatory frameworks rather than practical AI application development or software prototyping skills.