J'ai postulé via un établissement d'enseignement supérieur ou universitaire. J'ai passé un entretien chez Quantiphi en août 2022
Entretien
The interview process consists of 1 aptitide + 2 technical rounds (No HR round)
Aptitude round - Total of 80 questions ( 78 + 2 coding ( medium-level ))
First Technical Interview :-
The interviewer was very friendly and asked some basic questions about python and machine learning and AI (regularization, dropout layers etc.) and some questions regarding my project
Second Technical Interview :-
This interview was more focused on my work that I had done in my internships. The interviewer also asked some questions on a machine learning case study and in the end asked some easy coding questions to solve
Questions d'entretien [1]
Question 1
The interview process consists of 1 aptitide + 2 technical rounds (No HR round)
Aptitude round - Total of 80 questions ( 78 + 2 coding ( medium-level ))
First Technical Interview :-
The interviewer was very friendly and asked some basic questions about python and machine learning and AI (regularization, dropout layers etc.) and some questions regarding my project
Second Technical Interview :-
This interview was more focused on my work that I had done in my internships. The interviewer also asked some questions on a machine learning case study and in the end asked some easy coding questions to solve
J'ai postulé via un établissement d'enseignement supérieur ou universitaire. J'ai passé un entretien chez Quantiphi (Mumbai)
Entretien
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
J'ai passé un entretien chez Quantiphi (Palo Alto, LA)
Entretien
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
Questions d'entretien [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.
Questions d'entretien [1]
Question 1
ML algorithms and its working based on projects in resume.