- Supreet Kaur got a job offer from Microsoft after interviewing at 15 companies.
- After two years working in AI at Morgan Stanley, Kaur noticed a big shift in the market for AI roles.
- He emphasized the need for LLM experience, networking, and understanding a company's AI needs.
Supreet Kaur, 29, has interviewed at 15 companies in the past few months, and has received an offer from Microsoft.
Prior to his new role, he spent the past two years developing and managing data and AI solutions at Morgan Stanley. She said the job market for AI roles has changed a lot since she started looking for it about two years ago.
While big tech CEOs vie for AI talent, some candidates are fighting for a place in an increasingly competitive job market.
Kaur has a graduate degree in data science, worked in AI at a major bank, and is an ambassador for Google's WomenTechMakers program — and even said that when she first started her job search. They were not hearing anything from the companies.
Once Core made some changes in her approach, she was able to start seeing results and eventually landed a position at Microsoft as a Cloud Solutions Architect. If you're looking for a job in AI, Kaur said here are four important things you need to know.
LLM experience is now the industry standard.
Kaur said that when he interviewed for AI positions two years ago, companies were looking for machine learning experience. Now, companies are trying to create AI products. Companies are more eager to see if a candidate has worked with a chatbot or text classification system, he said.
Kaur said creative AI or LLM experience is now a basic requirement — and he didn't start hearing from interviews until he had mastered the area.
Once Kaur saw how many recruiters were asking for him, he volunteered at an organization and completed a three-month LLM project. While many applicants looking to enter the field now participate in AI workshops or bootcamps, Kaur suggests doing a project for use. Core built his enterprise-level project out of volunteer experience so he could talk about it in depth in interviews.
Cold applications may not work this time.
Kaur said he didn't send a lot of cold applications, but he didn't get a response from the ones he did send. Instead, she said she spent her time networking and contacting recruiters. She said she aims to send at least two messages and three to four personal connection requests each day.
He also tried to spread the word that he was looking for a job by telling people in a professional environment that he was on the market.
“The best way to find a job is when you don't need a job,” Kaur said. “You should go to events. You should go to meetings.”
come to the point
Kaur said that the mindset of companies has changed in the last two years. Today, they're looking for a much more specific experience, Kaur said.
“When I was interviewing in 2022, people were more interested in what I had done in data science,” Kaur said.
“All my interviews this time were very specific about what the companies wanted,” he added.
With companies' hiring portals flooded with qualified applicants, Kaur said they need to narrow things down. Kaur said he refined his search from product manager to solution architect when he realized his first attempt was too broad.
Core also recommends networking with workers at the company you're applying to and asking them what that company is looking for. He said it's crucial to understand their needs and what kind of experience they want in a particular candidate.
Having an online presence helps.
Core has also spent the last two years building an online presence.
He said he has spoken at dozens of events and many of them have led to subsequent interviews. It also helped him stand out in the application process.
“During our interview, some hiring manager said, 'You're the 100th candidate I've interviewed for this one position,'” Kaur said. “So it's obviously very competitive so it's important for you to stand out.”
Kaur said she started by contacting the university she attended and letting the professors know she was available to talk about her experience. From there, she was able to start building her following and book events regularly, including AI Summit New York, BNY Mellon, Re-Work New York, Women in Data Science Series, and Women in AI Series.