Staff / Principal Research Scientist, Models - USA

You don't need all of this. But you need enough to make a case.

• Foundation models: training, new architectures, RL, reward modeling, scaling
• Evaluation: benchmarks, eval loops, quality measurement, LLM-as-judge, failure analysis
• Frontier topics: multimodal models, agents, tool use, test-time compute, world models
• Published research at ICML, ICLR, NeurIPS, EMNLP, ACL, or AAAI
• PhD in ML/NLP — or equivalent practical experience you can point to
• Public work: non-trivial AI side projects, interdisciplinary experiments, open-source contributions
• Full-stack research ownership: you frame the question, run the experiments, write the paper, ship the result

If you learned through building, competitions, or collaborations outside academia, that counts. We care about evidence, not credentials.