# Research, RL Scaling at Thinking Machines

- Company: Thinking Machines
- What the company does: Connectionism: Research Blog by Thinking Machines Lab. Backed by a16z, Accel and GV.
- Company website: https://thinkingmachines.ai/
- Type: Startups (AI role)
- Level: Mid level
- Location: San Francisco
- Work setup: Remote
- Pay: $350K to $475K base salary per year (USD)
- Posted: 2026-08-21
- Apply by: 2026-10-08
- Apply: https://jobs.ashbyhq.com/thinkingmachines/0871bc29-7ca0-4906-a674-7b32527617ab
- Page: https://www.1752.vc/careers/jobs/thinking-machines-research-rl-scaling/

## About the role

Our team scales reinforcement learning for frontier models. Progress in RL is increasingly set by how well it scales: more rollouts, larger models, and training loops that keep large fleets of accelerators doing useful work. We are particularly interested in people working on high-training-compute, long-horizon RL. We believe the biggest gains come from designing the training recipe and the infrastructure together rather than separately, and we are hiring a researcher who wants to own that boundary.

## What they're looking for

- Proficiency in Python and familiarity with at least one deep learning framework (e.g., PyTorch, TensorFlow, or JAX). Comfortable with debugging distributed training and writing code that scales
- Bachelor’s degree or equivalent experience in Computer Science, Machine Learning, Physics, Mathematics, or a related discipline with strong theoretical and empirical grounding
- Clarity in communication, an ability to explain complex technical concepts in writing
- Strong research judgment: clean ablations, honest baselines, and clear technical writing
- Preferred qualifications — we encourage you to apply if you meet some but not all of these:
- PhD in Computer Science, Machine Learning, Physics, Mathematics, or a related discipline with strong theoretical and empirical grounding, or, equivalent industry research experience

Tags: Research