A Fireside Chat with a Machine Learning Researcher from Hugging Face

We had a chance to interview Nathan Lambert, a Ph.D. in Electrical and Electronics Engineering from UC Berkeley who’s now a Machine Learning Researcher at Hugging Face.

We worked with Nathan to negotiate his Hugging Face offer after graduating last year. In this interview, he talks about his transition from academia to tech. It was a great conversation!

We have included the recording below if you'd like to watch the whole interview - but we've also summarized our top 3 learnings in the next section.

Here are our top 3 learnings:

1. Deciding between academia or industry.
   Most STEM PhDs will face the decision of whether to go into industry or stay in academia. Nathan, as you may have guessed, chose industry. His motivation to pursue a career in industry (vs. academia) was his sense that the field is transitioning more towards the industry - he felt that there are now more exciting research opportunities and access to experiments within tech companies. Plus, he felt burned out from academia and was interested in a different pace of work.
   
   He also reflected that if he was committed to being a professor, staying on the academic track would have made more sense. Since he was not - he realized that staying on the academic track post-PhD to do more research, etc. would require lots of work and he’d be sacrificing opportunities to grow in the industry (as well as receive industry pay).
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2. Your network is your leverage. 
   When Nathan was asked what Ph.D. students should do to improve their opportunities to work in industry after graduating, he described two buckets: those who have access to networking at large tech companies and those that don’t.
   
   While networking opportunities often come through lab partnerships and events at schools, students should put effort into utilizing these and proactively building connections. 
   
   Those who don’t have those opportunities can start building their connections online: through open-source reproduction and cold emailing. Having industry connections as a graduate student is always an advantage.
   
   Nathan recounted his own experience as a combination of luck and hard work. One specific story he shared was how he worked hard on a machine learning project with a postdoc at Berkeley. The postdoc soon took a role at Facebook and eventually helped him get an internship there, too.
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3. Explore hot markets. 
   ‍The hiring market is shifting towards narrow industries such as early large language models and generative AI startups. He saw this when he was hired at Hugging Face last year along with other colleagues in the same industry while others in less niche markets struggled to find opportunities. 

As it relates to negotiation - Nathan is extremely happy that he advocated for increased pay and feels that he will be more confident in future negotiations. He described getting support to negotiate like going to therapy, where he learned things he was never taught and would have never realized that those were essential and useful until he was able to apply them. 

The two specific strategies that he found most helpful in his negotiation were:

1. After he got his job offer, he came up with an Impact Roadmap for what he wanted to accomplish in his role at Hugging Face and how he was planning to approach the work. He thinks this helped the company see him as more capable and allowed him to better showcase what he would bring to the table.
   
   
2. Since Nathan was new to negotiation, he didn’t realize how important timing and information control were to the outcome. Working with Rora helped him be intentional about what and when to share to ensure he didn’t accidentally give away leverage or share too much too soon.