The Google DeepMind Machine Learning Engineer interview process typically consists of three main stages. First, a phone screening involves discussing your technical background, past projects, and ML expertise. The second stage features in-depth evaluations, including technical rounds on machine learning concepts, algorithms, coding skills, and possibly domain-specific knowledge in areas like computer vision or NLP. Behavioral interviews assess collaboration and problem-solving skills. The final onsite stage comprises multiple rounds, including data structures and algorithms (DSA), machine learning system design, and leadership or HR interviews, sometimes involving a VP or senior leader. Throughout, candidates must demonstrate technical mastery, problem-solving ability, and alignment with Google's culture and values, often referred to as "Googleyness."

It was an internship. I was asked for Leetcode medium and hards, similar to "best time to sell stock" and DFS algos. The interviewers were really polite and supportive. I could not answer the graph algorithm.