Who Do You Actually Hire to Train a Model?

If you were building a team to train a model — not at OpenAI or DeepMind, but at a small lab or enterprise — who would you hire? The answer is stranger than the job postings suggest. At the engineering layer, titles are collapsing: Anthropic lists everyone as a Member of Technical Staff because the research/engineering boundary stopped being useful. At the data layer, they're multiplying: dataset engineers, licensing attorneys, annotation specialists. This episode walks through what each role actually does all day, which jobs fold into one person when you're small, and what happens when regulation — not fashion — drives demand for a career path that barely existed five years ago.

Key sources:

• The AI Roles Continuum, arXiv (2026) — https://arxiv.org/html/2601.06087v1

• Google, Assembling an ML team — https://developers.google.com/machine-learning/managing-ml-projects/team

• Anthropic, Research Engineer, Pretraining Scaling (2025-09-30) — https://job-boards.greenhouse.io/anthropic/jobs/4938432008

Episode 6030 — myweirdprompts.com/n/6030 (permanent short link: myweirdprompts.com/355716)