Machine Learning Engineer applicants have rated the interview process at Quantiphi with 2.9 out of 5 (where 5 is the highest level of difficulty) and assessed their interview experience as 68% positive. To compare, the company-average is 61.7% positive. This is according to Glassdoor user ratings.
Candidates applying for Machine Learning Engineer roles take an average of 5 days to get hired, when considering 60 user submitted interviews for this role. To compare, the hiring process at Quantiphi overall takes an average of 9 days.
Common stages of the interview process at Quantiphi as a Machine Learning Engineer according to 60 Glassdoor interviews include:
One on one interview: 24%
Skills test: 17%
Phone interview: 12%
Presentation: 10%
Personality test: 9%
IQ intelligence test: 9%
Background check: 8%
Other: 5%
Group panel interview: 4%
Drug test: 2%
Here are the most commonly searched roles for interview reports -
Interview had three rounds:
Round 1:
Online multiple choice questions - Deep Learning, Machine Learning, Data Science
Round 2:
Virtual Interview (Technical) - Deep Learning, Machine Learning, Data Science
Past experience
Projects and CV
Round 3:
Virtual HR Interview - Expectations and work culture discussion
Interview questions [1]
Question 1
CNN - final size of an image after passing through a 3x3 filter without padding
Activation function
Loss function
Gradient descent
Decision Tree and Random Forest
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.