A recent addition to the ranks of OpenAI, the creator of ChatGPT, shared her arduous journey to securing a position as an AI researcher, which involved an extensive search comprising 57 interviews with 11 different companies. Alisa Liu took to X to describe her experience as "really challenging but also super rewarding," and she hopes to demystify the process for future candidates through insights shared in a blog post.
As she concluded a six-year PhD program in natural language processing at the University of Washington, Liu focused her job applications on research scientist and technical staff roles within the AI sector. In addition to the intense interview process, she engaged in numerous informal networking chats, participated in 46 calls with recruiters, and had 16 discussions after receiving job offers.
Liu highlighted the emotional rollercoaster that often accompanies job searching, expressing that it was "stressful navigating a huge decision space with incomplete information." She noted how seemingly minor decisions could significantly influence her path. "Frankly, I was stressed, miserable, and not functioning in other parts of my life for several months," she admitted, encouraging others to remember they are not alone in feeling overwhelmed.
While Liu chose not to comment for Business Insider, an OpenAI representative confirmed her employment. In her blog, Liu provided a guide for those looking to enter the AI job market. She advised against burning out by applying to too many companies for practice interviews, emphasized the importance of choosing strategic timings for interviews, and highlighted the value of leveraging professional networks.
"To state the obvious: aim to excel during your PhD, build friendships, and collaborate frequently! Sometimes, getting that first interview requires someone within the company to endorse you," she noted.
Although having research experience can be beneficial for AI job seekers, Liu emphasized that companies often prioritize assessing technical skills and knowledge during the hiring process. Her interviews ranged from coding challenges in machine learning—her experience indicated these were the most frequently encountered questions—to technical discussions involving rapid-fire inquiries on advanced topics like 5D parallelism and positional encoding.
Liu's interview experiences also included research dialogues, behavioral questions, and math assessments, which featured a range of challenges from "fun logic puzzles to serious mathematical derivations with pen and paper." She recommended candidates refresh their knowledge in probability, linear algebra, and calculus.
Moreover, she stressed the importance of preparation for interviews, stating, "There is truly no better use of your time than studying for interviews," yet highlighted that getting a good night's sleep the evening before is irreplaceable.
Liu also pointed out that receiving job offers introduces its own complexities. She shared, "Negotiating is hard. Nothing in our PhD prepared us for this, and unlike interviews, this aspect cannot just be mastered through study." Investing time and energy into negotiation can translate into significant career benefits, she concluded, with results that could equivalent to years of effort stemming from an initial offer.
