1. Paper Review and Discussion
For the third round, you may be asked to review a paper and prepare for questions regarding it. Ensure you have thoroughly read and understood the paper, as it could be a topic of discussion during the interview.
2. Machine Learning Domain Knowledge Evaluation
In the second round, you will spend a significant portion of the interview discussing Machine Learning domain knowledge. Be prepared to delve deep into ML concepts and demonstrate your expertise.
3. NLP Coding Challenge
In the first round of interviews, you will also face a coding challenge related to Natural Language Processing. Be ready to write code that addresses a problem in the NLP field.
4. ML and NLP Domain Knowledge Assessment
During the first round of interviews, you will be assessed on your knowledge in the fields of Machine Learning and Natural Language Processing. Be prepared to discuss your understanding and approach to problems in these domains.
5. Discuss deep learning experience and behavioral questions
Discuss your experience with PyTorch, including the largest model you have trained and the largest model you have written from scratch. Share your career expectations and describe a challenging debugging situation you have encountered in the past.
