Member of Technical Staff - Distributed Training Engineer
Liquid AI, San Francisco
The role
Our Training Infrastructure team is building the distributed systems that power our next-generation Liquid Foundation Models. As we scale, we need to design, implement, and optimize the infrastructure that enables large-scale training.
This is a high-ownership training systems role focused on runtime/performance/reliability (not a general platform/SRE role). You’ll work on a small team with fast feedback loops, building critical systems from the ground up rather than inheriting mature infrastructure.
What you will do
The work
- Design and build core systems that make large training runs fast and reliable
- Build scalable distributed training infrastructure for GPU clusters
- Implement and tune parallelism/sharding strategies for evolving architectures
- Optimize distributed efficiency (topology-aware collectives, comm/compute overlap, straggler mitigation)