Skip to main content

Real Interview Experiences

Learn what to expect directly from candidates and interviewers who've been through it.

Updated 1 hour ago
Share your experience or upgrade to unlock access

Interviewed recently? Share your experience to try it free, or become a member for full access.

Meta
Machine Learning Engineer
Meta·Posted 1 month ago · Jun 2026

traditional interviews for MLE. coding rounds are AI-enabled meaning you can use claude or codex to write the code.

2 rounds2 questions
Read full interview
Cohere
Machine Learning Engineer
Cohere·Posted 2 months ago · Jun 2026

The system design interview was data collection, SFT and RL stages. It went well for me. It was focused on LLM post training techniques. The ML coding was worst for me although I practiced the same question but using PyTorch and doing without PyTorch and without any documentation was challenging for me.

3 rounds
Read full interview
Anthropic
Machine Learning Engineer
Anthropic·Posted 2 months ago · Jun 2026

The process is kind of cold. All tasks are performed on codesignal. You are basically do the assignment by yourself with the computer and camera on.

2 rounds
Read full interview
OpenAI
Research Engineer
OpenAI·Posted 3 months ago · May 2026

The problem was challenging. There were many conditions you had to satisfy and some aspects were a bit underspecified. The interviewers were stone faced and gave zero commentary. I ended up making a small bug which I wasted about 15 minutes trying to fix.

1 round
Read full interview
Google
Machine Learning Engineer
Google·Posted 1 month ago · Apr 2026

Interviewer was very comforting but focus on more Eval part. Prepare eval better along with failover strategy, model choices.

2 rounds2 questions
Read full interview
Microsoft
Machine Learning Engineer
Microsoft·Posted 1 month ago · Mar 2026

What went well: The live coding and system architecture rounds went smoothly. I was able to articulate my design choices clearly, especially around API design, database strategy, and maintaining high availability for microservices. What didn’t go well: The initial behavioral portion felt slightly rushed because we spent extra time discussing specific cross-functional project dynamics from my previous roles. How does this interview compare to other interviews you've done? It was significantly more interactive. Rather than giving static answers, the interviewers actively challenged my assumptions and asked "what if" scenarios, making the evaluation feel comprehensive and realistic to day-to-day work.

4 rounds6 questions
Read full interview
Apple
Machine Learning Engineer
Apple·Posted 2 months ago · Mar 2026

It was a good interview overall, I was just not prepared for it. Because it was a researcher role, i was first ask an my experience doing AI/ML research then we moved on to the technical problem, that I completely flunked because of nervousness and totally forgoing reviewing DS and Algorithms

2 rounds
Read full interview
Workday
Machine Learning Engineer
Workday·Posted 2 months ago · Mar 2026

The process was fairly quick. Recruiter gets back very fast. Good experience. All interviews completed within a week.

3 rounds
Read full interview
Google
Machine Learning Engineer
Google·Posted 2 months ago · Mar 2026

Went harsh and the interviewer was rude while asking the questions it was 45 mins but they extended it beyond 1 hr

3 rounds3 questions
Read full interview
formerly Exponent

Get updates in your inbox with the latest tips, job listings, and more.

Follow Us

Products
Courses
Interview Questions
Interview Experiences
Popular articles
Guides
Coaching
For Partners
Company
Exponent Labs, LLC © 2026
Terms of Service | Privacy