Machine Learning Engineer applicants have rated the interview process at Quantiphi with 2.1 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 34.5% positive. This is according to Glassdoor user ratings.
Candidates applying for Machine Learning Engineer roles take an average of 60 days to get hired, when considering 9 user submitted interviews for this role. To compare, the hiring process at Quantiphi overall takes an average of 29 days.
Common stages of the interview process at Quantiphi as a Machine Learning Engineer according to 9 Glassdoor interviews include:
Phone interview: 25%
IQ intelligence test: 20%
One on one interview: 20%
Presentation: 15%
Personality test: 10%
Other: 5%
Group panel interview: 5%
Here are the most commonly searched roles for interview reports -
I applied through college or university. I interviewed at Quantiphi (Mumbai) in Jul 2022
Interview
One aptitude round which includes logical, verbal and quantitative analysis questions in the first part and coding questions in the second, followed by the technical interview and then the HR round for final selects.
Interview questions [1]
Question 1
What is the difference between deep learning and machine learning?
I applied through college or 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.