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present of AI in San Francisco seeks a hands-on researcher to advance post-trained language models using reinforcement learning. You will design rewards, build multi-turn tool-using environments, and shepherd a project from dataset to deployed model, with an emphasis on understanding why methods work and how to scale them.
Ideal candidates have experience with RL methods like PPO or policy gradients, and can translate experimental results into production-ready systems.
present of AI in San Francisco seeks a hands-on researcher to advance post-trained language models using reinforcement learning. You will design rewards, build multi-turn tool-using environments, and shepherd a project from dataset to deployed model, with an emphasis on understanding why methods work and how to scale them.
Ideal candidates have experience with RL methods like PPO or policy gradients, and can translate experimental results into production-ready systems.