Vlad Feinberg is Google DeepMind’s pre-training area lead and I asked him all about how to land a job at a frontier lab like Google DeepMind, Anthropic or OpenAI.

• My ergonomic keyboard project I mentioned, you can follow along here: https://read.compose.llc/

• The Kickstarter page for it: https://www.kickstarter.com/projects/ryanlpeterman/compose-simple-ergonomics-beautifully-done

Podcast links:

• YouTube: https://youtu.be/cDyi91onoJ8

• Apple: https://podcasts.apple.com/us/podcast/the-peterman-pod/id1777363835

• Transcript: https://www.developing.dev/p/google-deepmind-pre-training-lead

Thank you to this episode's sponsor for supporting my work:

• WorkOS: makes your app Enterprise Ready with easy to use APIs to add SSO, SCIM, RBAC, and more in just a few lines of code, check them out at https://workos.com/

Timestamps:

(00:00) Intro

(00:33) Skills frontier labs need

(08:45) The difference between AI research and engineering

(21:41) Domains that matter for the frontier

(30:50) Marketing yourself to frontier labs

(35:13) Concrete steps engineers can take

(38:29) Overview of pre-training areas

(47:23) Jeff Dean spot bonus story

(50:14) Favorite Gemini war story

(58:59) Advice for his younger self

(01:03:07) Outro

Where to find Vlad:

• Personal Website: https://vladfeinberg.com/

• Twitter/X: https://x.com/FeinbergVlad

• LinkedIn: https://www.linkedin.com/in/vladimirfeinberg/

Where to find Ryan:

• Newsletter: https://www.developing.dev/

• X/Twitter: https://x.com/ryanlpeterman

• LinkedIn: https://www.linkedin.com/in/ryanlpeterman/

• Threads: https://www.threads.com/@ryanlpeterman

• Instagram: https://www.instagram.com/ryanlpeterman

• TikTok: https://www.tiktok.com/@ryanlpeterman

Referenced in this episode:

• How to Land a Job at a Frontier Lab: https://vladfeinberg.com/2026/05/10/how-to-land-a-job-at-a-frontier-lab.html

• ThunderKittens: https://github.com/HazyResearch/ThunderKittens

• Deedy's doomer Tweet: https://x.com/FeinbergVlad/status/2056383124829872466?s=20

• Jacob Steinhardt's "Research as a Stochastic Decision Process": https://cs.stanford.edu/~jsteinhardt/ResearchasaStochasticDecisionProcess.html

• The Scaling Book: https://jax-ml.github.io/scaling-book/

• Dwarkesh and Reiner's video: https://www.youtube.com/watch?v=xmkSf5IS-zw