The discovery of an AI product manager role at Netflix with a pay ceiling of $900,000 sent critics of the company and entertainment industry wild yesterday. That isn’t the only such listing, and likely not even the most lucrative. No one should be surprised that one of the biggest tech companies in the world is paying top dollar for machine learning talent — but that doesn’t mean striking writers and actors shouldn’t call out the hypocrisy on display.
So what are these jobs? In addition to the overall product manager one, there are five other roles with obvious machine learning responsibilities and likely more if you were to scour the requirements and duties of others.
An engineering manager in member satisfaction ML — their recommendation engine, probably — could earn as much as $849K, but the floor for the “market range” is $449K. That’s where the conversation starts! An L6 research scientist in ML could earn $390K to $900K, and the technical director of their ML R&D tech lab would make $450K-650K. There are some L5 software engineer and research scientist positions open for a more modest $100K-$700K.
One comparison that was quickly made is to the average SAG member, who earns less than $30K from acting per year. Superficially, Netflix paying half a million to its AI researchers so that they can obsolete the actors and writers altogether is the kind of Evil Corp move we have all come to expect. But that’s not quite what’s happening here.
While I have no doubt that Netflix is screwing over its talent in numerous ways, just like every other big studio, streaming platform, and production company, it’s important for those on the side of labor to ensure complaints have a sound basis — or they’ll be dismissed from the negotiating table.
The fact is that Netflix is among the largest and most successful tech companies in the world. While it is a novelty to have its name listed in the power acronym FAANG as well as next to megastudios like Disney and Universal, it also means that it must fulfill two sets of responsibilities.
As a tech company, Netflix is, like every other company on Earth, exploring the capabilities of AI. As you may have guessed from the billions of dollars being invested in this sector, it’s full of promise in a lot of ways that aren’t actually connected to the controversial generative models for art, voice, and writing, which for the most part have yet to demonstrate real value.
No doubt they are exploring those things too, but most companies remain extremely skeptical of generative AI for a lot of reasons. If you read the actual job descriptions, you’ll see that none actually pertain to content creation:
-You will lead requirements, design, and implementation of Metaflow product improvements…
-You will lead a team of experts in these techniques to understand how members experience titles, and how that changes their long-term assessment of their satisfaction with the Netflix service.
-…incubate and prototype concepts with the intent to eventually build a complete team to ship something new that could change the games industry and reach player audiences in new ways, as well as influencing adoption of AI technologies and tooling that are likely to level up our practices.
-…we are venturing further into exciting new innovations in personalization, discovery, experimentation, backend operations, and more, all driven by research at the frontiers of ML
-…Collect feedback and understand user needs from ML/AI practitioners and application engineers across Netflix, deriving product requirements and sizing their importance to then prioritize areas of investment.
-We are looking for an Applied Machine Learning Scientist to develop algorithms that power high quality localization at scale…
Sure, the last one is likely generative dubbing, or perhaps improved subtitle translation. And this doesn’t mean Netflix isn’t working on generative stuff too. But these are the jobs we’re actually seeing advertised, and most are generic “we want to see what we can do with AI to make stuff better and more efficient.”
AI applies across countless domains, as we chronicle in our regular roundup of research. A couple weeks ago it helped find new Nasca lines! But it’s also used in image processing, noise reduction, motion capture, network traffic flow, and datacenter power monitoring, all of which are relevant to a company like Netflix. Any company of this size that is not investing hundreds of millions in AI research is going to be left behind. If Disney or Max develops a compression algorithm that halves the bandwidth needed for good 4K video, or cracks the recommendation code, that’s a huge advantage.
So, why am I out here defending a giant corporation that clearly should be paying its writers and actors more?
Because if the unions and their supporters are going to take Netflix to task, as they should given the deplorable state of residuals and IP ownership, they can’t base their outrage on industry standard practices that are necessary for a tech company to succeed in the current era.
We don’t have to like that AI researchers are being paid half a million while an actress from a hit show a couple years back gets a check for $35. But this portion of Netflix’s inequity is, honestly, out of their control. They’re doing what is required of them there. Ask around: anyone with serious experience in machine learning and running an outfit is among the most sought-after people in the world right now. Their salaries are grossly inflated, yes — they’re the A-listers of tech right now, and this is their moment.
The problem is that by Netflix demonstrating its ability to do what’s needed in one area, they call attention to their failure to do what is required of them elsewhere — namely in support of creators, whose entire relationship with distribution platforms needs to be rewritten from scratch.
The threat of creators jumping ship and going to another streaming platform is very real. The next big indie horror hit is probably already working with A24 instead of one of the big guys because A24 gave the union everything they asked for. That’s 50 million dollars in the debit column because someone didn’t come to the table.
By all means let’s get up in arms about inequity — but if this anger is to take effect, it needs to be grounded in reality and targeted properly. Hiring an AI researcher for an extravagant salary to refine their recommendation engine isn’t the problem on its own — it’s the hypocrisy demonstrated by Netflix (and every other company doing this, probably all of them) showing that it is willing to pay some people what they’re worth, and other people as little as they can get away with. That’s a deliberate choice, and one that the striking creators hopefully can ensure is no longer possible in the future.