# Research Engineer, Infrastructure, Numerics 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/93855db2-9a80-421d-9e80-ace9eca24650
- Page: https://www.1752.vc/careers/jobs/thinking-machines-research-engineer-infrastructure-numerics/

## About the role

We’re looking for an infrastructure research engineer to design and build the core systems that enable efficient large-scale model training with a focus on numerics. You will focus on improving the numerical foundations of our distributed training stack, from precision formats and kernel optimizations to communication frameworks that make training trillion-parameter models stable, scalable, and fast.

## What they're looking for

- Bachelor’s degree or equivalent experience in computer science, electrical engineering, statistics, machine learning, physics, robotics, or similar
- 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
- Strong engineering skills, ability to contribute performant, maintainable code and debug in complex codebases in areas such as floating-point numerics, low-precision arithmetic, and distributed systems
- Preferred qualifications — we encourage you to apply if you meet some but not all of these:

Tags: Research Infrastructure (ML...