# Research Engineer, Infrastructure, Kernels 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: 2026-08-04
- Apply by: 2026-10-08
- Apply: https://jobs.ashbyhq.com/thinkingmachines/2d7a9e99-836a-475b-9ae3-b6b1df8baa6d
- Page: https://www.1752.vc/careers/jobs/thinking-machines-research-engineer-infrastructure-kernels/

## About the role

We’re looking for an infrastructure research engineer to design, optimize, and maintain the compute foundations that power large-scale language model training. You will develop high-performance ML kernels (e.g., CUDA, CuTe, Triton), enable efficient low-precision arithmetic, and improve the distributed compute stack that makes training large models possible.

## What they're looking for

- Bachelor’s degree or equivalent experience in computer science, electrical engineering, statistics, machine learning, physics, robotics, or similar
- Strong engineering skills, ability to contribute performant, maintainable code and debug in complex codebases
- Understanding of deep learning frameworks (e.g., PyTorch, JAX) and their underlying system architectures
- Thrive in a highly collaborative environment involving many, different cross-functional partners and subject matter experts
- A bias for action with a mindset to take initiative to work across different stacks and different teams where you spot the opportunity to make sure something ships
- Proficiency in CUDA, CuTe, Triton, or other GPU programming frameworks

Tags: Research Infrastructure (ML...