Gen AI Engineer applicants have rated the interview process at Infosys with 3 out of 5 (where 5 is the highest level of difficulty) and assessed their interview experience as 100% positive. To compare, the company-average is 69.1% positive. This is according to Glassdoor user ratings.
Candidates applying for Gen AI Engineer roles take an average of 15 days to get hired, when considering 1 user submitted interviews for this role. To compare, the hiring process at Infosys overall takes an average of 13 days.
Common stages of the interview process at Infosys as a Gen AI Engineer according to 1 Glassdoor interviews include:
Other: 33%
Personality test: 33%
One on one interview: 33%
Here are the most commonly searched roles for interview reports -
The Infosys Limited interview process is quite structured and consistent across roles. for freshers- sometimes online assessment test then Technical interview and HR interview
For Experienced Candidates
Data Scientist / ML roles, process can slightly expand:
1–2 Technical rounds (deep dive)
Managerial round (design + problem solving)
HR round
Interview questions [1]
Question 1
2 coding question and asked to code in preferred language, ML and AI domain questions on RAG, hallucination and project related questions
I applied through a recruiter. I interviewed at Infosys
Interview
Interview process was really easy, I got the call from HR and the interview was conducted. There was just one technical round and then the HR round that asked me about my notice period as well as my salary expectations.
Interview questions [1]
Question 1
Mostly questions were related to my project and the RAG.
I applied online. The process took 2 weeks. I interviewed at Infosys (Bengaluru) in Oct 2024
Interview
The interview process includes three comprehensive stages: starting with an online assessment conducted on the SHL platform to evaluate skills, followed by an in-person technical interview, and concluding with a detailed HR interview to discuss fit and expectations.
Interview questions [1]
Question 1
All the question related to the machine Learning Algorithm's,
Clustering
Linear Regression
K-means Clustering
K-Nearest Neighbors (KNN)