I applied through a recruiter. The process took 1 week. I interviewed at C3 AI (San Jose, CA) in July 2019
Interview
Contacted by recruiter on a job posting site that my profile and experience are quite matching for DS position(s) they have. Asked me to prepare a resume, apply online in the link provided and phone number (the usual first contact stuff from a recruiter). I did and we had a chat for about 15min. Basically I was asked 1) tell me about yourself and 2) what do you know about the company. Then I was told that he is going to forward the resume to HR and I should be contacted by HR for the next step in 3 days or so. Otherwise just send him a reminder. All I received after 3 days about was not proceeding further notice. Whoa! I contacted the recruiter however, did not get any response back as expected and remained curious about it.
One thing I noticed that typically recruiters explain the job, explain about the company and so on. In this particular case of mine, I only had those two questions (instead of him explaining the company and job profile, he was asking me what I knew). That was kind of unusual, later I felt. I did fail earlier in interviews in first step after they collect my resume however, recruiters were able to keep their words. I felt like being cheated on my efforts (on preparing resume etc.) in this case.
Anyways, the company has very broad portfolio and their valuation is pretty good as a start up. Their work look interesting as well. There are companies coming up in US completely focused on AI products and C3.ai is one of the leading ones.
Interview questions [1]
Question 1
Tell me about yourself.
What do you know about the company.
I applied online. I interviewed at C3 AI (Singapore)
Interview
Hackerrank --> three tech interviews (proceed to the next one if you pass the current one) each round is 1 hour long --> hiring manager interview (1 hour)--> VP interview.
Interview questions [1]
Question 1
tech interviews: 1) (1 hour) traditional ML based case study, 2) (1 hour) ML concept deep dive, and 3) (1 hour) coding (leet-code medium)
Resume screening -> technical assessment -> 4 rounds of interviews:
- personal projects, simple questions not there to trick you
- situational questions: "what would you do if..."
- machine learning: starts from the very basics (stats and probabilities) to more up to date models
- coding: medium leet code
I applied online. The process took 3 weeks. I interviewed at C3 AI (London, England) in Oct 2025
Interview
I applied directly after seeing a job advert on LinkedIn. There are MCQ and coding assessment on Hackerank, followed by a screening interview. It all went well and got invited to the technical day.
To prepare for the technical interview, I went through all materials and questions shared by others on this website and once I was half way, I noticed that the questions tend to be similar, except the pairwise coding. I recommend you go through questions here to be better prepared for the technical day.
The interview was generally okay and the team was nice. Started off with Case Study (30 mins); followed by ML questions (30 mins); and finally coding (1 hour). There is barely time in-between to switch so expect to transition very quickly. For the case study, think out loud it helped me to figure the actual problem, as they only share the problem and you figure the rest out.
The coding was fair, I had done a couple of Leetcode but they started off with Linear regression etc, kinda caught me off guard and wasted 35 mins on it. Though the program ran, the interviewer said there isn't enough time to complete second question, and we shared our coding experiences and clarity on a few questions. I am pretty confident in stats and ML knowledge but the issue could have been coding; so make sure you are up to speed with anything that can be thrown at you.
Two days later I received a rejection email. No reason after having spend so much time is a bit disrespectful but we move on.
Interview questions [1]
Question 1
Case study: Waste reduction in chain stores. They simply stated that and I described it as a demand forecasting problem that can be solved with Linear Regression. Besides clarification questions, It was fine and they took it.
MLQ
1. Difference between Supervised and Unsupervised Learning, and give examples
2. Difference between bagging and boosting;
3. Bias and variance, and explain in the context of Bagging/boosting
4. Performance metrics; what does AUC mean, interpret AUC of 50%
5. Gradient descent
6. Overfitting and Underfitting and how to overcome them in Decision Trees
Coding: Implement linear regression, numpy, and plotting importance scores