Real, anonymous reports from people who interviewed for AI Engineer at Turing, newest first and distilled into what to expect across the loop.
I started with an online coding round where I shared my screen and worked through the prompt live. A little later, I moved into a second round with an interviewer from a Google team format-wise, but the setup felt very practical: the interviewer had a CSV file and I was expected to write a simple data manipulation script from it.
I started with an online coding round where I shared my screen and worked through the prompt live. A little later, I moved into a second round with an interviewer from a Google team format-wise, but the setup felt very practical: the interviewer had a CSV file and I was expected to write a simple data manipulation script from it.
The interview process typically begins with an HR screening focused on the candidate's background and motivations, followed by a multiple-choice questionnaire assessing fundamental skills in programming and machine learning.
Candidates can expect a live coding round where they share their screen and solve problems, often emphasizing correctness and practical data manipulation tasks over complex algorithms.
Later rounds often involve deeper technical discussions, including system architecture and reasoning about larger technical designs, alongside algorithmic problem-solving challenges.
Candidates report a range of difficulty levels in coding challenges, with some finding the problems to be quite challenging, leading to stress and pressure during the assessments.
Overall, candidates noted that the interview atmosphere was generally supportive and non-adversarial, contributing positively to their experience despite the technical evaluations.
The interview process is described as structured and transparent, with clear expectations set for each stage, helping candidates understand what is being evaluated throughout.
