Tips for finding a job in the AI sector

Tips job seekers in the AI industry

The Al industry is hot right now. Experts share tips for finding a job in the sector.

The buzz around OpenAl’s ChatGPT has prompted some companies to consider how they can leverage the tech for specific business needs.

Big technology companies have laid off tens of thousands of workers in the past few months, but workers with skills in artificial intelligence are still in demand.

The hype surrounding ChatGPT and new search engines from Google and Microsoft is intensifying interest in artificial intelligence across many sectors.

The AI industry is vast, encompassing not only buzzy chatbots and conversational search engines but also things like self-driving vehicles. The excitement around OpenAI’s ChatGPT has already prompted some companies to consider how they can leverage the tech for specific business needs. Several news outlets, for example, have tapped the chatbot to generate some content.

“ChatGPT is a good example of how the barriers of using AI are dropping quite substantially and in a very rapid fashion,” Matthew Forshaw, a senior skills advisor at the Alan Turing Institute, told Insider.

For many companies, tools like ChatGPT could be used in an assistive capacity, managed by workers with knowledge of AI tech and ethics, Forshaw said.

Big technology companies have laid off tens of thousands of workers in recent months, but workers with AI skills are still in demand. Jim Monroe of Ada, an automation company specializing in customer service, said that a lot of companies “are still prioritizing AI roles both in terms of the hiring as well as if they are conducting layoffs.”

Insider spoke with five experts about breaking into the field. Here’s their best advice for jobseekers.

1. Build a strong foundation in math and computer science

Having a firm grasp of technical skills around deep learning can help candidates land AI roles with higher salaries.

Many high-paying jobs in the AI industry, such as data scientists and machine-learning engineers, usually require a minimum of a bachelor’s degree in a technical field such as computer science or math, experts previously told Insider.

Highly educated data scientists and core AI specialists with technical know-how are still highly in demand despite recent layoffs, Forshaw said.

Ngaire Moyes, LinkedIn’s UK country manager, told Insider that “machine-learning engineer” had been one of LinkedIn’s fastest-rising jobs in the UK for the past two years.

“As AI continues to become embedded into how many organisations operate day-to-day, it is a trend we anticipate will only continue to grow,” she said.

Some experts also recommend learning programming languages and gaining an understanding of AI frameworks, the programming interfaces that serve as building blocks to train and deploy AI models.

“Candidates do have to have baseline programming knowledge at some level,” Ada’s Monroe said. “Programming skills in Java, Python, PHP, C., or Ruby would be fairly common. Natural language processing is really hot right now, but data science and data analytics skills are still in high demand.”

Math and statistical analysis are also important skills for many AI roles, Monroe said. There is an analytic component to correlating data and predictability to ensure the AI is presenting the right answers or outcomes in specific business cases, such as customer service chatbots, he said.

2. Showcase your ability to solve real-world problems

Polo Chau, associate professor at Georgia Tech’s School of Computational Science and Engineering, told Insider that job candidates need to be able to articulate how classroom learning translated to the real world. “You need to connect the practical applications of what you know with the specific problems that your audience is trying to solve,” he said.

For instance, let’s say you participated in a hackathon where you created machine learning programs using different statistical techniques. You should be able to explain to hiring managers how you developed or invented or adapted techniques that led to a significant improvement, and that can be applied to solve a problem, Chau said.

“If you’re talking to a logistics company that’s trying to improve how it routes packages, you can talk about speed improvements. If you’re talking to a healthcare company that’s trying to figure out patient eligibility for studies, you can talk about fairness improvements. If you’re talking to a retailer that’s trying to understand customer trends, you can talk about accuracy improvements,” Chau said.

3. Develop strong presentation skills and cultivate an empathetic mindset

The most successful candidates have strong communication and presentation skills, Chau said.

“Throughout the pandemic, a lot of things have been virtual so people have not had the opportunity to present their work in front of a live audience,” he said. “Presenting on a screen when everyone is in a tiny box involves a different communication style and energy.”

Now that many conferences and networking events are in-person again, candidates need to perfect their elevator pitches. This is true for people looking to work in AI, but it’s also good advice for jobseekers more generally, too. “You need to have prepared a quick summary of what you’ve done,” he said. “And you need to practice it.”

A collaborative and empathetic approach is also key, Asu Ozdaglar, head of MIT’s department of electrical engineering and computer science, told Insider. “You need to know technical concepts around machine learning and algorithms and decision-making, but you also need to be asking, ‘How should those decisions take into account the human context?'”

ChatGPT’s growing popularity illustrates that point, Ozdaglar said. “In many cases these tools will be used to augment human decision-making. So when they’re deployed they not only need to be effective and efficient, but also reliable, fair, and equitable.”

4. Prioritize networking by attending events

As the AI arms race heats up across Silicon Valley, networking has become crucial to breaking into the industry.

Brianne Kimmel, a venture capitalist who founded the Silicon Valley based venture firm Worklife Ventures, said many of the conversations around AI are happening at small dinners or self-funded weekend hackathons. So, it can feel like AI is limited to insiders, she said.

“The technology is accessible to everyone, and no longer limited to PhDs who work at Google, but the deals getting done are happening quickly and quietly,” Kimmel said.

Still, Kimmel— who recently launched a bootcamp for AI startups— suggests that it’s best to jump in and learn alongside early builders. That’s especially true for those who want to break into AI in areas like marketing, sales, or as non-technical operators as there’s no need for formal education.

“My usual framing of the problem is we’re all figuring this out together,” Kimmel said. She invited a dozen women in tech to attend a recent OpenAI hackathon even though they weren’t all ready to make the leap to AI full-time.

“I think it’s super important to come and learn about the technology and to just hear and observe the types of companies that are being built,” Kimmel said. “Six or 12 months from now, if you decide to leave a company, you have exposure to what’s already been built, and areas with white space for starting a venture-scale business.”




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