ByteSimplified Development Intern (Cloud Computing) | Selected | India (Remote)
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CareerInterview

Application Details:

  • Company: ByteSimplified
  • Applied through Naukri
  • College: Tier 2, final year
  • Internship Period: 6 months
  • Work mode: Remote

Stage 1: HackerRank Screening
The initial screening involved two easy-level LeetCode-style questions to be solved in 30 minutes. Upon clearing this round, I was shortlisted for three interviews.

Round 1: Technical – Cloud Application Development (LLM-Assisted)
Duration: 60 to 75 mins
This round tested practical reasoning and the ability to use cloud tools and frameworks, with permission to use an LLM like ChatGPT.

The problem statement was to design a mini “Search-as-a-Service” prototype with the following requirements:

  • Build a lightweight search API using Flask or FastAPI with /upload and /search endpoints.
  • Implement an in-memory index (Whoosh or TF-IDF).
  • Deploy on AWS or Azure using any managed service such as Elastic Beanstalk or App Service.
  • Add logging and error handling.

Was able to implement and test in 1 hour, had few hickups but interviewer was helpful.

Round 2: Technical – Foundational Computer Science
This round consisted of 10 to 15 conceptual questions covering Algorithms, Data Structures, Operating Systems, Computer Networks, and Databases.

Some of the questions included:

Algorithms & Data Structures

  • You need to find the median of a continuously updating stream — how would you design for that?
  • What kind of data structure would you use to implement an “undo” feature in an editor, and why?

Operating Systems

  • When you open a new browser tab, what OS resources are created under the hood?
  • Why do deadlocks occur, and can the OS completely prevent them?
  • In what scenario could caching make your program slower instead of faster?

Computer Networks

  • Why might a video call prefer UDP over TCP, even at the cost of reliability?
  • When your browser shows “Secure” in the address bar, what technical chain of trust ensures that label?

Databases

  • How does an index improve query speed but potentially hurt bulk inserts?
  • When two transactions update the same record, what ensures you don’t end up with corrupted data?
  • How would you design a database to store time-series data like IoT sensor readings efficiently?

Round 3: HR and Fitment Discussion
A 30-minute conversation centered on my projects, technical interests, and goals. It was a decent discussion that assessed alignment and motivation.

Outcome: Selected

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