# Member of Technical Staff — Training Infrastructure at Causal

- Company: Causal
- What the company does: Backed by Accel.
- Company website: https://www.causal.app/
- Type: Startups
- Level: Senior
- Location: San Francisco
- Work setup: On-site
- Posted: 2025-10-29
- Apply by: 2026-10-08
- Apply: https://jobs.ashbyhq.com/causal/1ff002cd-87af-4dc8-88c4-786e4e03475d
- Page: https://www.1752.vc/careers/jobs/causal-member-of-technical-staff-training-infrastructure/

## About the role

Design, implement, and optimize distributed training systems that scale across thousands of GPUs Research and test parallelization strategies and numerical precision trade-offs across model scales, including for architectures that don't map cleanly onto existing LLM training stacks

## What they're looking for

- We value a relentless approach to problem-solving, rapid execution, and the ability to quickly learn in unfamiliar domains
- Demonstrated proficiency with distributed training frameworks and techniques (e.g. FSDP, DeepSpeed, Megatron, Pytorch, JAX/XLA) to train large foundation models
- Strong grasp of state-of-the-art techniques for optimizing training workloads: parallelism strategies, memory optimization, mixed precision, communication overlap
- Ability to profile and debug performance in complex codebases, from framework internals down to kernels and collectives
- Deep understanding of deep learning frameworks (e.g. PyTorch, JAX) and their underlying system architectures
- Bonus: contributions to open-source ML infrastructure (e.g. PyTorch, Megatron-LM, DeepSpeed, XLA)

Tags: Infrastructure