Companies Are Already Hiring for GPT-3 Skills
By: Frederik Bussler
Tags: Jobs, Artificial Intelligence, Machine Learning, Data Science, Hiring

Companies Are Already Hiring for GPT-3 Skills

Here’s a list — and how to get hired.

Photo by Magnet.me on Unsplash

In June, OpenAI started rolling out GPT-3, a state-of-the-art natural language AI that can create any kind of content, including code.

As of writing, around 15,000 people have been invited as beta users — a fraction of the roughly 300,000 AI researchers and practitioners around the world.

In short, given that relatively few people have access to GPT-3 and that the beta was released just half a year ago, I was surprised to find that companies around the world are already hiring for GPT-3 skills.

This trend is part of the broader “no-code AI” movement, and you’ll find that many companies are looking for other no-code skills like Webflow and Bubble. While GPT-3 is a powerful no-code AI for natural language, there are no-code AI tools like Obviously.AI for tabular data.

On LinkedIn

If you take a look at the LinkedIn Jobs page and search for “GPT-3,” you’ll find companies in a range of industries mentioning this state-of-the-art AI in the skills they’re looking for.

For example, Spaceflight Inc. is hiring for a Natural Language Processing Engineer, with desired skills including:

“Experience with Attention based NLP models such as BERT (and BERT derivatives) and GPT-2/3.”

Chipper Cash is hiring a Software Engineer, who will conduct tasks such as:

“Creating a GPT-3 powered ‘analyst’ Slackbot to make data accessible throughout the team.”

Alstom is hiring a data scientist with desired requirements, including:

“Experience in building NLP/NLU applications using free text and log files (spaCy, BERT, GPT-2/3, Transformers, Transfer Learning).”

Surprisingly, I even found intern positions requesting GPT-3 skills, such as this Ph.D. Data Science Internship at Vail Systems:

“Preference will be given to candidates with demonstrated proficiency in sentence-generative language models such as BERT and GPT-3.”

Takeda is hiring a Product Manager, specifying the following requirements:

“Experience in no-code/low-code platforms (bubble.io, glide, airtable, powerapps) as a prototyping tools, RPA (UIPath Studio/X), ML/NLP/CV, OpenAI GPT-3, Knowledge graph.”

Other job postings with GPT-3 requirements include:

A Deep Learning Research Engineer position at PUBG Corporation.

A Data Scientist role at ALTEN.

… and a surprisingly large amount of job postings in China (that I can’t read).

On Twitter

LinkedIn isn’t the only place to find jobs, and a lot of entrepreneurs are hiring on Twitter.

Naturally, OpenAI is hiring as well, and you’ll find their job postings through Twitter, LinkedIn, or the OpenAI page.

Networking

Recall that there are around 15,000 members with beta access to GPT-3 so far (this number is quickly growing — maybe it’ll be 150,000 by the time you read this).

While there aren’t nearly as many jobs officially listed, most jobs are never posted on job boards anyway. Instead, most jobs are filled through internal networks and referrals.

Because of this, networking within the AI community is perhaps the best way to find a job in the new GPT-3 industry.

Create Your Own Job

I recently came across a job title on LinkedIn that read “GPT-3 Prompt Engineer.” That job wasn’t even a possibility before the second half of 2020 (unless you work at OpenAI).

Every company exists to solve a problem, so if you can help them solve their problems (in an ROI-positive fashion), then you’ll likely be hired — whether there’s a job posting up or not.

Create a Startup

Yet another option is to create your own startup. OpenAI offers easy-to-use, input-output APIs that you can build a product around.

Keep in mind, however, that forming a startup is incredibly risky. There’s a large opportunity cost, financial cost, mental cost, and time cost, without any guarantees of any kind of positive return.

It’s said that around 90% of startups of fail, but the true number is likely closer to 99% (if 10% of projects make it to incorporation), or more likely 99.9% (if 1% of projects make it to incorporation).

In any case, this high risk also comes with the potential for high reward. A GPT-3 powered startup, Otherside AI, recently raised $2.6 million. Some GPT-3 startups are already seeing upwards of $30,000 MRR (!), and that’s only what I’ve seen publicly.