Machine Learning Engineer Intern applicants have rated the interview process at TuSimple with 3.7 out of 5 (where 5 is the highest level of difficulty) and assessed their interview experience as 33% positive. To compare, the company-average is 64.5% positive. This is according to Glassdoor user ratings.
Candidates applying for Machine Learning Engineer Intern roles take an average of 14 days to get hired, when considering 3 user submitted interviews for this role. To compare, the hiring process at TuSimple overall takes an average of 25 days.
Common stages of the interview process at TuSimple as a Machine Learning Engineer Intern according to 3 Glassdoor interviews include:
One on one interview: 25%
Skills test: 25%
Background check: 13%
Phone interview: 13%
Personality test: 13%
Presentation: 13%
Here are the most commonly searched roles for interview reports -
I applied online. The process took 2 weeks. I interviewed at TuSimple (Buffalo, NY) in Apr 2022
Interview
From the beginning since I got the HR screening call it didn't look like they wanted to hire me anyways but still scheduled the interview. After the HR screening call they scheduled the interview but the interviewer didn't show up for the call, so they rescheduled it to next week. Only one person from TuSimple showed up and started the interview. It looked like he wanted me to fail the interview and not the other way around.
Interview questions [1]
Question 1
Numerous questions about my one major project and then started telling me what I should've done, which is okay I like constructive criticism. After that started asking ML and DL concepts like a rapid fire round and literally stopped the interview when I got a question wrong as if he was waiting for me to just fail.
Leetcode coding question and some Machine learning system design. The problem on LeetCode is the Max Area of Island problem. The Max Area of Island problem is a common graph theory problem and a classic question on LeetCode. In this problem, we are given a matrix consisting of 0's and 1's, where 1 represents land and 0 represents water. An island is defined as a series of adjacent land cells (horizontal or vertical). We need to find the island with the maximum area, i.e., the island that contains the most land cells, and return its area. One common approach to solving this problem is to use depth-first search (DFS) or breadth-first search (BFS). Specifically, we can start the search from each land cell in the matrix and record the current island's size during the search. Finally, we can compare the sizes of all islands and return the one with the maximum area.
I applied online. I interviewed at TuSimple (San Diego, CA) in Dec 2020
Interview
The first round is coding. I solved two problems.
The second round is resume interview. The interviewer asked me questions about deep learning and projects. I think I answered most of questions well.