Ho presentato la mia candidatura tramite un'agenzia di reclutamento personale. La procedura ha richiesto 3 giorni. Ho sostenuto un colloquio presso LTIMindtree (Bengaluru) nel mese di mar 2022
Colloquio
Questions on past experience and the project in the previous organization . Two technical and one HR round for the entire interview process. Second round of technical interview questions were in depth questions in machine learning.
Domande di colloquio [1]
Domanda 1
1. Forecasting Techniques used 2. what is convolution layer 3. what is stride 4. what are vectorization techniques u used in the project.
Ho presentato la mia candidatura tramite un selezionatore. Ho sostenuto un colloquio presso LTIMindtree
Colloquio
The interview process consisted of a total of three rounds. The first round was a technical interview focused on core technical skills and problem-solving abilities. The second round included both technical and managerial discussions. The final round was an HR interview covering general discussions, company policies, and salary-related details.
Ho presentato la mia candidatura online. Ho sostenuto un colloquio presso LTIMindtree nel mese di ott 2025
Colloquio
Interview Process was smooth. HR calls and asks for details and then Technical round happens with LTI mindtree client.If we clear this offer then we get offer. Questions are around ML, AI, NLP techniques , focuses more on projects we worked on.
Domande di colloquio [1]
Domanda 1
1. Give brief about yourself.
2. Explain any project you have worked on based on ML,AI,NLP.
3. Did you face any hallucinations? How did you handle them?
4. How did you get the accuracy? Human evaluation?
5. What is self attention in transformer model?
6. Difference between stemming and lemmatization in NLP?
7. Named entity recognition?
8. What is part-of-speech tagging?
9. Any ML project, classification?
10. How do we decide root node for decision tree?
11. Imbalanced Dataset? How is it handled?
12. TFID vectorizer ? how does it work?
13. Deep Learning algorithm
14. what is vanishing gradient issue in DL?
15. Pooling or filters in DL?
16. Topic modeling in NLP.
4 people panel asked questions regarding machine learning deep learning transformers models a little about Gen Ai. Checking deep knowledge around all topics. The question are hard but can be cleared if someone have deep knowledge the model and why certain situation arise and what to do in that kind of situations
