Ho presentato la mia candidatura online. La procedura ha richiesto 2 mesi. Ho sostenuto un colloquio presso IBM (Bengaluru) nel mese di dic 2020
Colloquio
Profile - Machine Learning/ NLP
Timeline:-
1. Application Submitted - 1st Dec 2020
2. Shortlisted for Technical Interview - 16th Dec 2020
3. Technical Interview - 23rd Dec 2020
4. Cognitive Ability Test (Cognify) - 13th Jan 2021
5. PDM Interview - 15th Jan 2021
6. Interview Results - 3rd Feb 2021
Technical Interview Questions were Resume based.
PDM Interview Questions were both technical as well as HR based.
Domande di colloquio [5]
Domanda 1
Q: 1. Questions related to projects and internship
Q: 1. What is Expectation of a random variable?
Q: 2. Explain the Bias - Variance Trade-Off
Q: 3. Project-related question
Q: 4. Have you ever collaborated on Projects? (To check Team player skills)
Q: 5. How would you give a presentation on an AI-based project to an audience which does not understand AI?
Q: 6. Why Research?
Q: 7. Why IBM Research Lab?
Ho presentato la mia candidatura tramite un'altra fonte. Ho sostenuto un colloquio presso IBM (Tel Aviv) nel mese di gen 2026
Colloquio
Interview with 2 researchers from the team
asked a code question and want them to tell about a paper I published, explain the process, methodology and the results. also tell a crisis I had in team and how I handled
Ho presentato la mia candidatura tramite l'università. Ho sostenuto un colloquio presso IBM (Nuova Delhi)
Colloquio
It was a 1 hours interview process which involved the teams who have shortlisted you via resume, will ask you certain question based on their team's work and fundamentals so cant really tell what can they ask
1st interview - your interests, reason for application, general background stuff
2nd interview - assessment of coding skills, AI concepts, LLMs, etc., using problem scenarios (goal is to understand problem solving skills)
Seems to depend on each team and members on the team
Domande di colloquio [1]
Domanda 1
Why are you interested in IBM Research? Questions related to machine learning pipeline, what models you would use for the problem, etc.