Head of Fine-Tuning Science & Frontier ML

Thinking Machines Lab; San Francisco (CA); On-site; USD 475,000 - 530,000; Full time

Benefits offered by this job

Health, dental, and vision benefits

Unlimited PTO

Relocation support

Parental leave

Job summary

Thinking Machines is building AI tools to extend human will and judgment, including Tinker, the leading post-training engine, with a focus on frontier customization techniques. The role leads the Fine-tuning Science team, shaping the research agenda while remaining hands-on in science and model development.

You’ll work with internal research groups, contribute to open science, and engage with external users, driving progress from research to shipped capabilities.

Qualifications

• Bachelor’s degree or equivalent 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.

Responsibilities

• Advance the science of fine-tuning and frontier post-training techniques.
• Set the research agenda: choose problems, place 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.

Skills

Leadership in research

Python programming

PyTorch

TensorFlow

JAX

Technical communication

Interest in custom models

Education

Bachelor’s degree or equivalent in CS/ML/Physics/Math

Tools

PyTorch

TensorFlow

JAX

Job description

Thinking Machines is building AI tools to extend human will and judgment, including Tinker, the leading post-training engine, with a focus on frontier customization techniques. The role leads the Fine-tuning Science team, shaping the research agenda while remaining hands-on in science and model development.

You’ll work with internal research groups, contribute to open science, and engage with external users, driving progress from research to shipped capabilities.