Chip Huyen’s 4 AI and ML Job Search Tips

Chip Huyen is the co-founder of Claypot AI, a real-time machine learning (ML) platform, and author of bestselling computer science books, including: Machine learning system designpublished last May, and helpful e-books such as Introduction to machine learning interviewsShe is an Adjunct Lecturer at Stanford University and previously worked at Snorkel AI and Nvidia.

But Huyen is also on the committee that runs MLops Learners. MLops Learners is her community of over 12,000 dedicated to learning and sharing ML Productions (MLops) best practices and hosting virtual and in-person events.

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There, she said, Huyen helps the group’s Discord community. There is a lot of discussion about job hunting right now. The most skilled and popular artificial intelligence (AI) and ML talents.

AI and ML job seekers on the rise

“I think it’s a little scary for a lot of people,” she said. “Now it turns out that she’s one of the most popular channels on Discord taking her career advice.”

Posting on Discord is anonymous, allowing participants to share their fears and anxieties privately. “We hope that we can provide an outlet for people to express themselves and that others will speak up.”

She noted that even if someone hasn’t been fired, even if a colleague has been fired, there’s a sense of, “Am I next?”

“It’s a very natural instinct to start looking,” she said. “So we are seeing a shift in the market from an employment perspective.”

But she added that while the market itself is leading people to take less risk, there is often uncertainty about which roles to pursue now.

“Someone said recently that they got an offer from their hometown and another from the UK,” she said. “Two years ago they were very excited to go to a new country and start. So it’s true that people tend to be hesitant to take risks, even if they get a really good job at a big company abroad.”

What AI and ML Job Seekers Can Do Now

Huyen emphasized that there are several things job seekers looking for their next AI or ML job can do to land the right position. There may be differences depending on the type of company or industry a candidate applies to, but overall it’s all about making yourself more robust and agile in the face of change, she said.

1. Differentiate yourself.

First and foremost, Huyen says, think about how you can differentiate yourself from other AI and ML job seekers. “I see a lot of resumes and a lot of them are exactly the same,” she said. “[One candidate] In fact, I told you I’ve put 4,500 hours into Python. But metrics don’t mean anything out of context. ”

It’s true that automated resume screening often requires some of these types of metrics, but for a startup like Claypot AI, a cookie-cutter resume doesn’t help. She encourages candidates to be creative with side projects because she believes there is a lot of value in having interesting ideas and showing creativity in thought.

2. Focus on transferable skills.

Huyen explained that non-transferable AI and ML skills are very specific, such as knowing the details of specific frameworks and tools. They may not be transferable to other companies. For example, programming languages ​​like COBOL, which are now obsolete. “Our scope of work changes over time, so we want to look for more applicable skills,” he says. “So we want people who know only one thing, but who have a set of skills that make them understand anything: design thinking, how to ask the right questions, how to articulate ideas. Or you can figure out what’s wrong, so if something goes wrong, you’re not stuck.”

3. Cover data engineering best practices.

In a recent LinkedIn post, Huyen welcomed the rise of the data engineer role. “More and more data scientists are adopting best engineering practices (by choice or need) and moving into data engineering. The data engineer role may be in higher demand than the data science role !”

“I always make the mistake of getting better through engineering,” she said. “Machine learning is more specific, but with a good engineering foundation, like systems thinking, you can learn anything.”

4. Consider a generative AI side project.

“Generative AI is a very exciting field and I think there are many opportunities to build products on top of them. [tools]’ said Huwen. “So if anyone is looking for a project, I highly recommend it. It’s a place where you can get a lot of creativity, not just sit at the keyboard and do what you’re told. .”

It’s also an area with a lot of potential, she added. However, in my opinion, this is still an unexplored area. ”