Startups · AI

Research, Tinker, RL Systems

Thinking Machines · San Francisco · Remote

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About Thinking Machines

Connectionism: Research Blog by Thinking Machines Lab. Backed by a16z, Accel and GV.

About the role

Tinker is our fine-tuning API that empowers researchers and developers to customize frontier AI to their needs to open access to capabilities that have previously been concentrated in a handful of labs. We manage the infrastructure while allowing Tinkerers full flexibility in training models with their own data, algorithms, and for their own needs. This role is all about building our training systems for Tinker, including RL systems, numerics, kernels, and beyond.

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
  • 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
  • Strong interest in working on Tinker and increasing usefulness and adoption
  • Preferred qualifications — we encourage you to apply if you meet some but not all of these:
  • A strong grasp of probability, statistics, and ML fundamentals. You can look at experimental data and distinguish between real effects, noise, and bugs
More about this role

The mission of Thinking Machines is to build AI that extends human will and judgment. We are training frontier models with Inkling, developing Tinker to let people make models their own, and crafting interfaces that broaden human-AI communication. We believe the future worth building is human, and we're hiring people who want to build it.

Tinker is our fine-tuning API that empowers researchers and developers to customize frontier AI to their needs to open access to capabilities that have previously been concentrated in a handful of labs. We manage the infrastructure while allowing Tinkerers full flexibility in training models with their own data, algorithms, and for their own needs.

This role is all about building our training systems for Tinker, including RL systems, numerics, kernels, and beyond.

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...

Read the full posting on Thinking Machines's site ↗

Research

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