I applied through university. The process took 3 days. I interviewed at Quantiphi (Mumbai) in Sept 2020
Interview
I had to go through two rounds of interviews, one being a technical interview and one being a HR interview. However, both involved technical questions. Being a Mechanical Engineer, the level of interview questions were adjusted to my knowledge level, and the interviewers in both the rounds were encouraging and friendly. Being my first interview through my college placement process, it was a great learning experience for me, even though I was not shortlisted for a job. The questions I faced were mainly technical, related to regression, the types of A.I. and their applications, how would I improve the accuracy of an A.I. visual inspection system in a manufacturing plant, etc. Thus, to me it appeared as though they expect a basic understanding of A.I. methods and applications and some projects in the field from engineering freshers. If you have some experience with A.I. related projects and are interested in the field, I would encourage you to apply to this company either through your college placements if possible, or otherwise they also have a separate freshers section on their job application portal. All the best!
Interview questions [1]
Question 1
Discussion on regression, the types of A.I. and their applications, how would I improve the accuracy of an A.I. visual inspection system in a manufacturing plant, etc. Tested basic understanding of A.I. and methods, and expected projects related to A.I. in the resume.
I applied through university. I interviewed at Quantiphi (Mumbai)
Interview
4 Rounds
1 - Test -> Aptitude, CSE Fundamentals, Coding
2 - Technical Round 1: Resume based questions and some fundamentals of ML and AI
3 - Technical Round 2: Resume based questions and indepth questions on architectures, frameworks and fundamentally important parts
4 - HR
Pretty easy basic ml question and transformer architectures , no leetcode or ml system design questions, Transformer architecture encoder decoder and autoregressive models Transformer architecture encoder decoder and autoregressive models
Interview questions [1]
Question 1
Transformer architecture encoder decoder and autoregressive models
The process has three rounds: one aptitude test, one technical round on ML basics, algorithms, logical reasoning puzzles, project-related questions, and one HR round focusing on reasoning behind ML model choices.
Interview questions [1]
Question 1
ML algorithms and its working based on projects in resume.