Ho presentato la mia candidatura tramite segnalazione di un dipendente. Ho sostenuto un colloquio presso Oracle (Bengaluru)
Colloquio
1. Telephonic round - covered all basic core java online questions 2. Technical discussion - was good, problem solving questions on Arrays and Strings, asked to implement own Hashmap and about Webservices 3. Managerial round with technical discussion - About current working project 4. HR round
Domande di colloquio [1]
Domanda 1
Core java concepts including tricky questions and working of different collections, Java 8, Problem solving, Web services
Technical Prep: Data Structures & Algorithms (DSA)
Oracle commonly asks Easy to Medium-level questions on HackerRank, focusing on efficiency and code quality.
Key Topics: Arrays, Strings, HashMaps, Linked Lists, Binary Trees, and Graphs.
Common Problems: Inverting a binary tree, merging sorted arrays, and finding the first non-repeating character in a string.
Focus: Practice communicating your thought process out loud ("think out loud") and optimizing for both time and space complexity.
Ho sostenuto un colloquio presso Oracle (Bengaluru)
Colloquio
1st round elimination.
4 rounds of loop interview.
Loop rounds- 1 DSA Hard
HLD
LLD
Bar Raiser round.
Interview experience was average. First interviewer was not supportive in DSA. In spite of giving 3 solutions, he wanted to hear one that he had predetermined
La procedura ha richiesto 4 settimane. Ho sostenuto un colloquio presso Oracle (Zürich, Zürich) nel mese di giu 2025
Colloquio
Was for a position at one of their labs and took a bit under a month.
1. Screening call with HR with basic behavioural/experience question.
2. 2x technical interviews (LLMs, parallelism, databases, etc) with coding components.
3. Hiring manager interview (behavioural, technical).
Overall the interviewers were timely, pleasant and reasonable. Often they asked questions about many different areas and went more in depth based on my experience.
Domande di colloquio [1]
Domanda 1
Describe 3 different optimisations applied to LLM inference.
