Ho presentato la mia candidatura online. Ho sostenuto un colloquio presso Wipro
Colloquio
Always HR reschedules the interview . I was interviewed for AI/ML but they didn't ask any one question related to that. They asked only one python program and expected to do it in old format with loops and without any inbuilt function.
Domande di colloquio [1]
Domanda 1
Tell me about urself. python program without inbuilt function.
They focused more on theoretical questions rather than project based. Also, one coding question is given during the interview. Try to deep dive on all the skills you have mentioned on resume.
Domande di colloquio [1]
Domanda 1
How does transformer work and what will change if we make changes in encoder decoder blocks?
Ho presentato la mia candidatura tramite un selezionatore. Ho sostenuto un colloquio presso Wipro nel mese di giu 2025
Colloquio
Interview process was smooth. Two technical rounds where basic python and AI ML concepts were asked . There were some scenario based as well as project based questions. The next round was client round which was much more difficult than wipro internal rounds. Indepth knowledge of GenAI was tested. Overall the experience was good. Talent acquisition who was processing every steps made the process very smooth and fast
Domande di colloquio [1]
Domanda 1
How RAG works, Why do we need vector database, what was the chunk size you used in project, why did you use that chunk size, How BERT works and its limitations, a practical code to find second largest element in list using python and much more
Ho presentato la mia candidatura online. La procedura ha richiesto una settimana. Ho sostenuto un colloquio presso Wipro (New York, NY) nel mese di apr 2025
Colloquio
The interview process at Wipro for the AI/ML Engineer role was structured and thorough. It included an initial HR screening, followed by two rounds of technical interviews. The first technical round focused on core ML concepts, Python coding, and problem-solving. The second round involved scenario-based questions on deploying ML models, MLOps, and working with cloud platforms like AWS. The final round was a managerial discussion focused on team collaboration, project experience, and cultural fit. The interviewers were professional, and the process moved efficiently.