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The AI Hiring Landscape is Booming
Despite the tech industry's inundation with layoffs (hundreds of thousands in 2023 alone), demand for AI talent is accelerating. In particular, there are three areas still recruiting such talent:
- New industry research labs like Anthropic, Inflection, and Altos Labs continue to raise hundreds of millions in funding to recruit talent. Although hiring has slowed in the traditional labs at Google, Meta, etc. compared to five years ago, these organizations are still growing.
- Venture-backed AI-focused startups have accelerated hiring since the advent of ChatGPT. We expect this hiring to continue, as VCs have a lot of capital to deploy; they're likely to invest heavily despite the economic conditions. Per the New York Times, interest in AI “has mounted so rapidly that A.I. start-up valuations are soaring beyond that of 2021’s ‘everything bubble,’ with investors trawling the rosters of companies like Google, Meta, and OpenAI for A.I. experts who may have an itch to start their own company.”
- Outside of the tech world, industries like finance, healthcare, and science are also all seeking machine learning researchers to apply this new technology to their space.
Your PhD program may feel saturated with researchers, but you’re in luck: the global demand for these skills vastly outweighs the actual supply. In 2021, there were just 1,691 PhDs awarded in computing research, according to a Taulbee survey. In the United States alone, there is a need for 33,5000 computer and information research scientists - and demand is increasing 21% a year! That means that each year, there are approximately 5,000 more research scientist jobs than there are research scientists to fill them.
So, knowing this, how do you ensure you land the best offer and negotiate top terms?
What Do Companies Value?
First, you’ll want to learn which research areas companies value the most. Right now, the highest demand lies in the application of machine learning to computer vision (autonomous & visual), robotics, natural language processing (NLP), biology, and neuroscience. With the introduction of ChatGPT, a background in large language models (LLMs) has become a hot new skill set. Companies like Meta are launching generative AI-related teams for language, image, and video generation.
You’ll also need to understand what companies consider when evaluating candidates. For an AI researcher, proven research skills are paramount. One area this shows up is your publication record. The top researchers will have as high as 2,000 citations just from their PhD and an H-index of 10. You do not need to have this strong of a publication record to negotiate successfully - every researcher has leverage to negotiate - but the top researchers can negotiate more senior roles and the top compensation we share below.
On a similar note, hiring managers will want to see your papers selected by top AI conferences like NeurIPS, ICML, ICCV, etc. Companies also care about work experience outside of academia. Internships signal that you are able to adapt to the industry environment and aren’t an ivory-tower academic.
Finally, doing research for the professors who run academic labs and are also industry research directors helps you build relationships in the industry while you’re in school. Computer Science is a unique academic field that intersects greatly with the private industry. It’s not uncommon for professors to also be research directors, such as Yann Lecun, who runs a lab at NYU and is the Chief AI Scientist at FAIR.
Highest Paying Companies for AI Researchers
We’ve negotiated industry offers with over 610 new grad PhD researchers, the details of which are in the table below. The majority of this data line up with entry-level research opportunities (equivalent to L4 at Google), but some clients have successfully negotiated above entry-level offers.
The total compensation included in this table comprises base salary, bonus, and equity. Be aware that signing or other cash bonuses can range from $0 to $700k over a four-year period, but are not included in this table. To give a clear picture of how low companies’ offers can start, we included the initial offer along with the final, negotiated compensation.
*This offer was not from a Rora client, but was validated from a trusted source.
It’s clear that companies like Anthropic, Tesla, OpenAI, Google Brain, and Amazon provided the highest initial offers (and were willing to negotiate a higher final deal), but the companies that increased their offers the most are Google Research, Microsoft Research, Bloomberg AI, IBM Research, and TikTok. What you can take away from this is that even if your initial offer is low, there’s always room to use your leverage as a highly-skilled researcher to land a better offer.
Understand the Financial Stakes
It’s important to understand that the stakes, even for an entry-level offer in AI, are high. Negotiation is arguably the highest-ROI work you’ll do in your entire career.
If you’re a new grad PhD receiving an L4 Research Scientist offer from Google, you could earn as much as $550k per year - or as low as $250k per year. That’s quite the difference, and it doesn’t only impact your first year of employment. The impact of successful (or unsuccessful) negotiation compounds over time.
Think about it like this: imagine two people start out with a $100k salary offer. Person A negotiates better and lands a 5% higher offer than Person B. Fast forward to 25 years in the future, and in order for Person A and Person B to have equal earnings, Person B would have to work 14.27 additional years. This doesn’t take into consideration all the other aspects of compensation like annual bonus, equity, signing bonus, paid time off, and any relocation stipend.
One of our clients received an offer whose equity package was so far below that of her peers - by hundreds of thousands of dollars - that even with stellar performance, the maximum possible raises didn’t even come close to closing her gap. As a result, she had to leave the company. She may have been able to stick it out with lower pay for a while, but the long-term impact and the money she’d lose over time made it impossible to stay.
Don’t let this fuel more negotiation anxiety; instead, use this knowledge to recognize the investment you should make to empower yourself to negotiate well.
Understand the Professional Stakes
When you think about negotiating, chances are you think about the compensation you’re offered when you take the job - and you stop there. It’s true that negotiating your initial compensation is valuable, but it’s even more important to understand how to negotiate once you’re inside the company. The offer is just the beginning.
What does that mean? Just as your PhD advisor is a critical element of your academic success, your relationships with managers and leaders are critical for industry success. Understanding how to influence others leads to better projects; more visibility; and ultimately promotions, career growth, and pay raises over time. When you’re ineffective at negotiating inside the company, you’re at risk of conflict with your manager (regarding your performance or your pay); being stuck with projects with low visibility or low impact; failure to achieve raises or promotions; or even potentially losing your job.
More important than compensation, it’s critical for the goal of negotiating to be to build an alliance with your manager - an alliance where your career benefits increase as you continue doing great work. Creating a win-win negotiation builds the foundation for employment success once you start. Think of the offer negotiation process as the first impression you make before the influencing and advocating you’ll need to do on the job.
Negotiation Result from Our Clients
Negotiation is a skill that takes a lifetime to master, and we’re always learning and improving. Here are a few real stories from Rora clients to add to your knowledge bank and help you prepare for your next negotiation.
A 243% Increase: Google Research Scientist Negotiation
Joe, an AI research scientist with PhD research in machine learning and a few industry internships under his belt, received an offer from Google (where he'd interned) for $216k/year. With Rora’s help, Joe turned that offer into total compensation of $526k a year.
Now, it’s true that Joe was an impressive candidate by virtue of his in-demand skill set, but it’s worth noting he did not attend a top 20 AI research institution. His publication record was average. He also didn’t have as much prior work experience as some of our clients, yet he was able to land a 243% increase. How did he do it?
First, he knew his worth - and that this was a lowball offer. Companies frequently offer less than they’re capable of paying; this may seem dishonest, but it’s a practicality. Compensation isn’t a meritocracy, it’s a market, so it’s important to be ready to argue for what you want. Based on our data, we advised Joe to respond with an expectation of $500k/year. When Google demurred, Joe requested an updated offer deadline, and he then used that time to interview at other companies. At the end of this three-month process, he had two offers in hand, each in the $300k range. Using those competitive offers, Joe convinced Google to up their offer to $356k - but he didn’t give up there!
Joe knew that at this point, it was all about leverage. He did his due diligence and negotiated higher offers from the other companies. This required patience and a lot of back-and-forth, plus pressure from recruiters who just wanted Joe to accept their offers. Ultimately, he turned this leverage into a $526k offer from Google.
Rora gave Joe greater insight into his market value and possible negotiation tactics, but what sealed the deal was the relationships he had built. His final Google offer required executive approval as it was outside the standard compensation band, but because Joe had built a strong relationship with his boss and boss's boss during his internship, getting that approval was no problem.
The takeaways are these: patience, leverage, conviction, and relationships. The process to reach a final offer can be long, so the ability to remain patient is key. You need to know - and communicate - your leverage throughout the negotiation. Stay convicted about what you need and don’t settle for less, even if a recruiter pressures you to make a decision. And always have a champion; a good word from someone inside the company, especially if they're in a position of power, can make all the difference.
For more detailed client experiences, check out the links below:
- Two Common Mistakes When Negotiating a Machine Learning Engineer Salary
- Facebook and Google Research Scientist Salary Negotiation
- DeepMind, Google, and Databricks Research Engineer Salary Negotiation
- LinkedIn & Google Data Scientist Salary Negotiation
- Walmart Labs Senior Data Scientist Salary Negotiation
- FAIR and DeepMind Research Scientist Salary Negotiation
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