Research Lead, Tinker, Fine-tuning Science

Job summary

Responsibilities

At Thinking Machines we build tools that enable people to make AI their own, customizing models to serve their unique needs. This includes the ability to train model weights.

• Set the research agenda: choose the problems, place the bets, and own the roadmap for pushing Tinker quality, efficiency, and reliability to the frontier.
• Lead and grow the team: hire, mentor, and develop researchers, and set the bar for experimental rigor and research taste.
• Stay hands-on in areas like LoRA and parameter-efficient fine-tuning and how they interact with RL and post-training.
• Improve the stability, efficiency, and reliability of large-scale fine-tuning and RL runs on Tinker.
• Represent the work externally through papers, technical blog posts, and community contributions.

What they're looking for

• Bachelor’s degree or equivalent experience in Computer Science, Machine Learning, Physics, Mathematics, or a related discipline with strong theoretical and empirical grounding.
• A track record of leading research – setting direction for a team or a major research effort and delivering on it.
• Proficiency in Python and familiarity with deep learning frameworks (e.g., PyTorch, TensorFlow, or JAX). Comfort debugging distributed training and writing code that scales.
• Clarity in communication: an ability to explain complex technical concepts in writing and to build alignment across science, systems/infra, product.
• Strong interest in our mission to enable custom models.

Tech stack

• Python
• PyTorch
• TensorFlow
• JAX