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The ultimate guide to getting a job in AI

Recruiters who specialize in finding candidates for AI roles at OpenAI, AWS, and Uber share their advice for applicants.

The ultimate guide to getting a job in AI
[Source photo: Rawpixel]

Investors are pouring money into the Artificial Intelligence industry. And now, the AI sector is offering some of the most exorbitant salaries in tech.

AI-related startups raised close to $50 billion last year, according to Crunchbase data, with certain companies, such as OpenAI and Anthropic, raising billions all on their own. A 2023 survey by Biz Report determined that AI-related jobs can offer job-seekers 77% higher salaries on average than other occupations, with some starting salaries as high as $450,000 a year.

But how does one actually land an AI-related job in this AI boom? What do recruiters who hire for AI-focused roles even look for, given that this space is relatively new?

I interviewed three recruiting leaders from OpenAI, Uber, and Amazon Web Services (AWS) to pull back the curtain and help you get hired. Here’s what they had to say.


Before you create a game plan for how you are going to land the job, you must understand what AI roles are even out there.

Robert Infantino led diverse-research recruitment at OpenAI and spearheaded research hiring for AWS AI. He says that the main AI roles include “applied and fundamental research scientists and engineers, software and data engineers for infrastructure, technical product and program managers, and hardware engineers.”

Some firms such as Runway, an applied research company making a content-creation platform for artists and creatives with the use of Generative AI (GenAI), are building machine learning and applied research teams with a focus on computer vision and generative media, says Lauren Saltus, a technical recruiter at Runway who has more than seven years of recruiting experience.

Before you dive into a company’s career page, Saltus recommends that you “understand that some companies are doing end-to-end research and development, while others are focusing on implementation of existing research for various products, which will impact the roles companies are hiring for.” Knowing what kinds of roles you are looking for can help you narrow your search and find an organization that is the right fit for you.


When recruiting and hiring for AI roles, Nikita Gupta, a former senior technical recruiter at Uber and founder of Careerflow.ai, focuses on three key areas: “a strong background in math and statistics, proficiency in programming skills commonly used in AI and machine learning, and a solid understanding of machine learning algorithms.”

Aside from concrete skills and experience, AI-job recruiters also look for soft skills such as curiosity and optimism, shares Saltus. To gauge these qualities in an applicant, she asks candidates: “Are you excited to learn and grow? What side projects are you tinkering with? Do you meet challenges with a solutions-oriented mindset?” And she explains that her team is “pushing the boundaries of innovation and looking for people who thrive in this type of environment.”

Infantino says that he “generally looks for signals of exceptional ability, which could range from winning the Math Olympiad in high school to chairing the New York Philharmonic or even playing professional poker.”

Candidates also stand out if they can demonstrate “velocity of career progression, working alongside the best in the field, and having highly influential papers accepted at top conferences or journals,” he adds. Infantino calls this characteristic “high slope,” meaning an applicant shows signs of ambition, building something meaningful, taking risks, and moving the needle in their field or company.


While other industries like tech are laying off workers, AI-related roles are spawning faster than the talent available

“Over the past few years, the demand for AI talent has experienced significant growth and evolution,” says Gupta, “driven by advancements in technology, increasing adoption of AI across industries, and the growing recognition of the value that AI can bring to businesses.”

Gupta has noticed three key trends in the demand for AI talent: the number of job postings for AI-related roles has been steadily increasing across industries, competition among companies to attract and retain top talent has intensified, and specialized and advanced roles (such as AI ethics, AI security, AI infrastructure, and AI product management) have emerged.

The battle for top tech talent is only continuing to heat up as “tech giants, startups, research institutions, and other organizations are all vying for skilled AI professionals, leading to competitive salaries, benefits, and perks,” Gupta explains.


Recruiters tell me that as the demand for AI talent has increased, new challenges have surfaced including a dearth of diversity and senior-level talent.

“The main challenges include very few women in the AI space, the lack of relevant skills and knowledge, and the intense competition of talent between big tech,” says Gupta.

Saltus says her team at Runway is not just aiming to diversify their talent pools, but also thinking about how to promote DEI values within their AI model, allowing them to have the ability to positively impact diverse representation in media.

Saltus adds that hiring senior talent for AI roles is also difficult. “Since it’s such a new industry, there aren’t a ton of people with senior-level expertise,” she says. “Although there are a lot of folks looking to get into the industry now, it doesn’t solve the current challenge with everyone racing to be the ‘industry leader.’”


Given that there is limited AI talent on the market, recruiters must get savvy with how they find and source workers.

For example, we know that recruiters are hungry for applicants with AI research experience. So Saltus says her teams’ most effective strategy for attracting top-tier AI talent is “building our research brand in the industry and letting the product (and research) speak for itself. This means more of a focus on publications and industry involvement.”

Companies are also introducing unique programs to attract and incubate talent. For instance, Runway offers an acceleration program—“a full-time, paid program that allows folks from diverse backgrounds to transition into machine learning roles through a guided mentorship program.”

Saltus emphasizes that AI models are evolving at a rapid pace, and her team believes that “strong technical skills, the ability to learn fast, and the courage to dive into unfamiliar challenges and technologies, are far more important than a formal education in the field.”

Recruiters should “invest time in learning and, at least conceptually, understanding technology as the first big step in sourcing talent,” says Infantino. “I’d recommend staying abreast of the rapid developments in state-of-the-art via X/Twitter and tech media and then working backward from who’s building it. Understand citation analysis and how to assess researchers’ profiles and papers, and utilize platforms like Google Scholar, Aminer, Hugging Face, and Github to find talent through their work.”


Job seekers should be aware that recruiters use AI to fill AI roles.

AI in the workplace has skyrocketed. A survey by the Society for Human Resource Management found that 80% of organizations use AI for hiring and recruiting.

Simply put, “the future of recruiting truly lies in our ability to adapt, learn, and utilize new tools,” says Saltus, arguing that these tools are meant to enhance the process of finding the best talent to fill roles rather than replacing human judgment.

Infantino also tries to automate much of his rote work, “using many of the popular LLM products for tasks like finding and synthesizing information and organizing my calendar.” He assures that he doesn’t automate the interpersonal aspects of recruiting as it’s “value over volume for me.”

Recruiters like Infantino claim that AI can offer several advantages in the recruitment process. For example, speed to hire, reducing bias, lowering cost, improving quality of hire, accessing global talent, offering a better candidate experience, and integrating with an employer of record.


Now that you know what AI roles exist and how recruiters source talent, what are the best tricks for breaking into these exclusive AI roles?

Saltus recommends “taking an active part in the community. One of the primary reasons the AI industry has evolved so quickly is its openness in research. Those taking part in discussions that further our understanding of this technology and its advancements are the first ones I’d want to speak with.”

Infantino advises candidates to “start side projects and collaborations” if their current role doesn’t offer the opportunity to work on bleeding-edge technology. You should be deliberate about networking and building relationships in the AI field by “attending conferences regularly, actively contributing to popular code repositories, and meetups,” he adds.

As with any role, even outside AI, Infantino says that candidates must “be strategic and give yourself every opportunity to showcase your skills in front of the most credible people in your field. Their cosign could go a long way in landing your next role.”

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