Research, Finetuning Science

Thinking Machines Lab builds AI that extends human will and judgment through frontier models, model customization tools, and human-AI interfaces. The role advances fine-tuning and frontier post-training techniques, integrates research into the Tinker product, improves large-scale training reliability, and shares findings through research and community contributions.

Responsibilities:

• Contribute to areas like LoRA and parameter efficient fine-tuning and how to push customization quality, efficiency, and reliability to the frontier
• Ship research into product: inform Tinker's training defaults and primitives, and codify best-practice methods as recipes in the Tinker Cookbook
• Improve the stability, efficiency, and reliability of large-scale fine-tuning and RL runs on Tinker
• Share what you learn through papers, technical blog posts, and community contributions
• You’ll contribute to areas like LoRA, parameter-efficient fine-tuning, how things interact with RL and post-training, and how to push customization quality, efficiency, and reliability to the frontier