Member of Technical Staff - Training Infrastructure Engineer

Work at Liquid AI, a foundation model company spun out of MIT CSAIL, and contribute to building efficient AI systems at every scale. Collaborate with world-class engineers, researchers, and builders to shape the frontier of intelligent systems.

Requirements

• Extensive experience building distributed training infrastructure for language and multimodal models
• Hands-on expertise in frameworks like PyTorch Distributed, DeepSpeed, or Megatron-LM
• Deep understanding of hardware accelerators and networking topologies
• Ability to optimize communication patterns for different parallelism strategies
• Skilled at identifying and resolving performance bottlenecks in training pipelines

Benefits

• Opportunity to solve hard systems challenges in AI
• Experience building infrastructure that powers next-gen foundation models
• Satisfaction of seeing work directly enable breakthroughs in model capabilities and performance