I just wrapped up my interview at OpenAI for an ML engineer role. The process was intense but exciting. We delved into cutting-edge ML concepts, focusing on large language models and multimodal AI. They grilled me with tough technical questions and scenarios. I also shared my thoughts on AI ethics and my vision for the field's future. Overall, it was a challenging but stimulating experience.
Questions d'entretien [1]
Question 1
How would you build an LLM powered enterprise search system?
This whole process dragged on for about a month, much longer than I anticipated. It kicked off with a technical phone screen, where I was asked about data structures and algorithms. The DSA questions were tough, especially one regarding matrix traversal. Mid-way through the coding round, it clicked that I had tackled this exact problem on PracHub just days before, which helped me structure my answer. The onsite included system design questions that were challenging, but I didn’t end up receiving an offer. Overall, it was an intense experience.
Questions d'entretien [1]
Question 1
Given an n x n matrix where each row and each column is sorted in ascending order, return the kth smallest element in the matrix. Walk through both the min-heap approach and the binary-search-on-value approach, compare their time and space complexity, and discuss which one you'd prefer for very large matrices that don't fit in memory.
2 rounds phone screen(1 coding + 1 system design) and 4 rounds onsite interviews(1 coding + 1 design + 1 deep dive + 1 behavior).
general good experience but need fast coding
J'ai postulé via une autre source. J'ai passé un entretien chez OpenAI (Dublin, Dublin) en mai 2026
Entretien
Two hiring manager interviews. Followed by a technical interview on coding and system design. Asked to design a devbox system (CI/CD pipeline). For the coding roundm I was asked to design the LRU/LFU cache.
Questions d'entretien [1]
Question 1
I was asked to design the LRU/LFU cache.
design a devbox system (CI/CD pipeline).