Hiring: Member of Technical Staff - Distributed Training Engineer Company: Liquid AI Location: San Francisco, CA Job Posted Time: 2026-09-10 10:30:51 Target Skills & Keywords : Data Pipeline, PyTorch About the job Experience: •Hands-on experience building distributed training infrastructure (PyTorch Distributed DDP/FSDP, DeepSpeed ZeRO, Megatron-LM TP/PP) •Understanding of hardware accelerators and networking topologies Required Skills: •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. •Loves distributed systems complexity: Our team builds systems that keeps long training runs stable, debugs training failures across GPU clusters, and improves performance. •Wants to build: We need builders who find satisfaction in robust, fast, reliable infrastructure. •Thrives in ambiguity: Our systems support model architectures that are still evolving. We make decisions with incomplete information and iterate quickly. •Aligns with team priorities and delivers: Our best engineers align with team priorities while pushing back with data when they see problems. •Design and build core systems that make large training runs fast and reliable •Build scalable distributed training infrastructure for GPU clusters Qualifications: •MoE (Mixture of Experts) training experience •Open-source contributions to training infrastructure projects •What Success Looks Like (Year One) •Overall training efficiency/cost has improved •Training stability has improved (fewer failures, faster recovery) •Data loading bottlenecks are eliminated for multimodal workloads Interested candidates, please apply directly through the job posting on company's career page or try via AI auto apply on this platform. Don't miss this opportunity to join a forward-thinking team!