Interviewing with Hummingwave Technologies for a Software Development Engineer (SDE) position was one of the most enriching technical discussions I’ve had so far. The interview lasted around 50–55 minutes and covered a spectrum of topics — from fundamental OOP concepts and database management to a deep, detailed discussion around the projects on my resume.

I’m happy to share that the experience went well, and I ultimately secured the offer. Here’s a detailed walkthrough of the interview.

The Process

The interview began with a short personal introduction from both sides. I was asked to walk the interviewer through my background, technical interests, and key projects. This quickly set the tone for a conversation that was both technical and exploratory.

1. Object-Oriented Programming (OOP)

A significant portion of the early interview revolved around OOP. The interviewer focused more on conceptual clarity and practical usage than theoretical memorization. mutiple question were asked based on class, Object,and overal OOPs concept.

2. Database Management Systems (DBMS)

Though not the primary focus, the interview did assess my understanding of database fundamentals and real-world data design.

Deep Dive into My Projects

This was the longest and most detailed segment of the interview. The interviewer wanted to understand the depth of my involvement, my problem-solving approach, and the reasoning behind my technical decisions.

A. Plant Recognition System

###Questions What dataset did you use and how did you prepare it? Why did you choose your specific model architecture? How did you handle class imbalance? If accuracy drops under low-light conditions, how would you improve robustness? How would you reduce inference time without significantly affecting accuracy?

B. Movie Recommendation System

Did you use collaborative filtering, content-based filtering, or a hybrid approach? What features did you extract? How did you compute similarity between users or movies? How do you measure the performance of a recommender system? How would you solve the cold-start problem for new users? How would you scale the recommendation pipeline as data volume grows?

C. Camouflaged Object Detection

This project attracted special attention due to its complexity and uniqueness.

Questions :

What makes camouflaged object detection a challenging task? Which model architecture did you use? How did you evaluate model performance? If objects blend almost perfectly with their surroundings, how can the model be improved? How would you adapt your model for real-time video detection?

I think they were evaluating my understanding of model optimization, domain challenges, data processing, and deployment considerations.

This is the end of questions.

The interview concluded with a short discussion about:

My preferred tech stack How I usually debug issues My willingness to learn new tools and adapt They also allowed me to ask questions about the role, team structure, and company culture.

Final Result

After some days, I received the confirmation that I had been selected for the SDE role at Hummingwave Technologies. The interview was well-structured, conversational, and intellectually engaging.

What stood out most was the company’s emphasis on understanding thought process over memorized answers. This experience circulated around the importance of strong fundamentals combined with practical, hands-on project knowledge.