Thinking Machines Lab
Research, Finetuning Science
$350K–$475K
San Francisco · On-site · Full-time · Posted Sep 16, 2026
- Education
- Bachelor’s degree or equivalent experience; a PhD or equivalent industry research experience is preferred.
- Visa sponsorship
- Visa sponsorship is offered; success is not guaranteed for every candidate or role.
About the job
Advances fine-tuning and post-training research, translating findings into Tinker product features, training guidance, and open-science contributions.
What you'll do
- Research LoRA, parameter-efficient fine-tuning, and related customization techniques to improve quality, efficiency, and reliability.
- Inform Tinker’s training defaults and primitives, and document best practices in the Tinker Cookbook.
- Improve the stability, efficiency, and reliability of large-scale fine-tuning and RL runs; share findings through papers, technical posts, and community work.
What they ask for
- Bachelor’s degree or equivalent experience in Computer Science, Machine Learning, Physics, Mathematics, or a related discipline, with strong theoretical and empirical grounding.
- Proficiency in Python and familiarity with deep learning frameworks such as PyTorch, TensorFlow, or JAX; able to debug distributed training and write scalable code.
- Clear written communication and ability to explain complex technical concepts.
- Strong interest in the mission to enable custom models.
Nice to have
- Experience with RLHF, RLAIF, preference modeling, or reward learning for large models; or RL training stability techniques for large runs.
- PhD or equivalent industry research experience; experience with human-data workflows, alignment, data-centric AI, or human-AI collaboration.
Pay
$350,000 - $475,000 USD annual salary (base salary)
Tools
Python, PyTorch, TensorFlow, JAX, LoRA, Tinker
AI focus
Researches fine-tuning, RL, and frontier post-training to customize models and improve Tinker’s training capabilities.
Model-written summary · the original posting is authoritative