Google is losing top AI talent at a rate that should worry anyone watching the company closely. According to Bloomberg, two senior researchers, Jonas Adler and Alexander Pritzel, are departing Google for Anthropic. Both played key roles in building Google’s Gemini model.
The news, first reported by Bloomberg, comes just days after a string of other high-profile exits that have put Google’s talent pipeline under a microscope. This is not a one-off. It is starting to look like a pattern.
The most striking recent departure was Noam Shazeer, one of the most respected AI researchers in the field. Shazeer spent most of his career at Google, joining in 2000, before leaving to co-found Character.AI. Google paid $2.7 billion to effectively bring him back, acquiring the startup’s technology and key staff to work on Gemini. He has now left again, this time for OpenAI.
Then came John Jumper, a director at Google DeepMind. Jumper shared the 2024 Nobel Prize in Chemistry with DeepMind CEO Demis Hassabis for their work on AlphaFold, a system that predicts 3D protein structures from amino acid sequences. He is also heading to Anthropic.
So in a short window, Google has lost:
- Noam Shazeer, a long-time Google veteran and AI pioneer, now at OpenAI
- John Jumper, Nobel Prize winner and DeepMind director, now at Anthropic
- Jonas Adler and Alexander Pritzel, core Gemini contributors, also headed to Anthropic
The timing matters. Both OpenAI and Anthropic are preparing to go public, which means they can offer equity packages that are suddenly very attractive. For a researcher weighing options, joining a pre-IPO company with real momentum is a compelling deal, regardless of what their current employer pays them in salary.
For Google, this is more than a PR headache. These are not junior hires. These are people who built the systems Google is betting its future on. Replacing that kind of experience and institutional knowledge takes years, not months.
Google has not commented publicly on the departures. But the broader question the company now faces is whether this is a temporary rough patch or a sign that the most ambitious AI researchers see more opportunity elsewhere.
