# The Process There was a test before the interview that consisted of aptitude and English grammar sections, followed by a technical interview. The technical interview mostly revolved around my projects and some CS fundamentals. Questions were asked from topics such as computer networks, OS, and DBMS. # My Thoughts and Advice Most of the aptitude questions were of easy to medium difficulty, but the English grammar section was quite difficult. The interview is easy to clear if you can explain your projects clearly and confidently.

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.

I had been practicing DSA on LeetCode for around two years, solving the Striver SDE Sheet twice to strengthen my problem-solving skills. Along the way, I explored multiple programming languages — Python, Java, C/C++, Solidity — and worked with technologies like MERN stack, blockchain, machine learning, and deep learning. In the last 6 months, I also started learning system design fundamentals, which helped me approach Visa’s technical rounds with confidence. This broad preparation allowed me to adapt quickly during their challenging selection process. ### Recruitment Process Overview Visa’s selection process had four rounds: 1. **Online Assessment (DSA)** 2. **Technical Interview 1** 3. **Technical Interview 2 (System Design)** 4. **Team Lead Round** The rounds tested my problem-solving, technical knowledge, system design understanding, and communication skills. ### Round 1 – Online Assessment (DSA) This round had **four DSA questions**, testing algorithmic and coding abilities. After this round, 8 students were selected for the next stage. ### Round 2 – Technical Interview 1 This round started with a self-introduction followed by a **20-minute discussion on my projects**: * Describing my projects and selecting the best one * Challenges faced and improvements possible * **SQL and DSA questions** * Discussion about my **LeetCode rating (~1887)** and algorithms The interviewer asked about choosing the right algorithm, evaluating pre-existing code, and managing code quality. Despite initial nervousness, I received confirmation to move to the next round (6 students selected). ### Round 3 – Technical Interview 2 (System Design) This round focused on **scalability and system design**. The discussion included: * Choosing a project example from my resume * Designing a high-level architecture (HLD) * Components like **load balancer, cache, API gateway, database, microservices, rate limiter** * Ensuring **high availability, low latency, and scalability** My preparation in system design basics helped me confidently discuss design decisions, and the interviewer complimented my strong fundamentals. After this round, 5 students advanced. ### Round 4 – Team Lead Round This was a **communication-focused round**. Clear articulation and asking relevant questions based on previous rounds helped me stand out. The discussion went smoothly, and the interviewer was impressed with my insights and preparation. ### Key Takeaways * **Consistency pays off:** Years of DSA practice and project work laid the foundation. * **System design knowledge matters:** Early preparation made technical 2 round easier. * **Communication & curiosity:** Clear explanations and asking the right questions made a difference in the final round. * **Luck helps:** Being able to tie answers from previous rounds added value. ### Outcome One day later, I received the **offer from Visa at 35 LPA** — a dream come true!