Glassdoor users rated their interview experience at Moonshot AI as 100% positive with a difficulty rating score of 3 out of 5 (where 5 is the highest level of difficulty). Candidates interviewing for LLM engineer and rated their interviews as the hardest, whereas interviews for LLM engineer and roles were rated as the easiest.
The interview process at Moonshot AI was thorough and engaging. It began with an initial screening call to discuss my background and interest in the role. This was followed by a technical assessment that tested my problem-solving skills. The final round was a panel interview with senior team members, where we discussed potential use cases for AI and ethical considerations. Throughout the process, the team was professional and made me feel comfortable sharing my ideas.
Interview questions [1]
Question 1
They asked me about my approach to handling ethical dilemmas in AI development. I responded by emphasizing the importance of transparency, continuous learning, and collaboration with experts in ethics to ensure responsible AI practices.
I applied online. The process took 4 weeks. I interviewed at Moonshot AI (Shanghai, Shanghai) in Feb 2023
Interview
At Moonshot AI, our interview process for a Senior Software Engineer is straightforward: after applying online, candidates take an online test, followed by a phone or video interview. If they do well, they'll have an on-site technical interview and meet with potential team members. The final step is an HR interview before we make a job offer. We value candidates' questions throughout the process.
Interview questions [1]
Question 1
Can you describe a complex problem you've encountered in a past project and how you approached solving it?
Pretty standard, very nice interview , they were respectful and try to encourage you in the process. Was hoping they might have deeper expertise in the field but they just use the industry standard which makes me worry what's their competitive advantage
Interview questions [1]
Question 1
What’s DPO PPO , talk about your past research experience