Research, Tinker, RL Systems

Thinking Machines builds AI designed to extend human will and judgment through frontier models, customization tools, and human-AI interfaces. The Research, Tinker, RL Systems role focuses on developing training systems for Tinker, including reinforcement learning systems, numerics, kernels, and post-training pipelines. The role involves co-designing RL algorithms, debugging and optimizing training runs, and supporting internal researchers, external partners, and users in achieving frontier-level results.

Responsibilities:

• In this role, you'll develop frontier customization techniques and help build the best post-training engine in the industry, drawing on a whole-stack understanding recipes, data pipelines, and training systems (numerics, kernels, and beyond)
• You'll engage directly with the researchers and companies pushing Tinker to its limits. This role is working with both our internal research teams as well as contributing to open science and external partners
• You’ll co-design RL algorithms and training systems across the whole stack, from RL science down to numerics and kernels, to enable anyone to post-train frontier models. You’ll debug RL runs in the wild, optimize post-training pipelines, and help users reach frontier-level results, which in turn makes our platform and models the best they can be