Member of Technical Staff - Training Infrastructure Engineer

🕒 Agosto 9, 2025

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Liquid AI

SiteLinkedInTodas as Vagas

51 - 200 funcionários

Fundada em 2023

🤖 Inteligência Artificial

🤝 B2B

🏢 Corporativo

Artificial Intelligence • B2B • Enterprise

Liquid AI é uma empresa de tecnologia de ponta que se especializa em soluções de inteligência artificial nativas da borda. Seus inovadores Modelos de Fundação Líquida (LFMs) são projetados para oferecer IA eficiente e personalizável para diversos ambientes—desde computação de borda até infraestruturas em nuvem. Ao maximizar a eficiência computacional e aproveitar arquiteturas avançadas de redes neurais, a Liquid AI fornece às empresas soluções de IA flexíveis e poderosas, adaptadas às suas necessidades específicas.

Descrição

• Design and implement high-performance, scalable training infrastructure that efficiently utilizes our GPU clusters for both specialized and large-scale multimodal models • Build robust data loading systems that eliminate I/O bottlenecks and enable training on diverse multimodal datasets • Develop sophisticated checkpointing mechanisms that balance memory constraints with recovery needs across different model scales • Optimize communication patterns between nodes to minimize the overhead of distributed training for long-running experiments • Collaborate with ML engineers to implement new model architectures and training algorithms at scale • Create monitoring and debugging tools to ensure training stability and resource efficiency across our infrastructure

🎯 Requisitos

• You have extensive experience building distributed training infrastructure for language and multimodal models, with hands-on expertise in frameworks like PyTorch Distributed, DeepSpeed, or Megatron-LM • You're passionate about solving complex systems challenges in large-scale model training—from efficient multimodal data loading to sophisticated sharding strategies to robust checkpointing mechanisms • You have a deep understanding of hardware accelerators and networking topologies, with the ability to optimize communication patterns for different parallelism strategies • You're skilled at identifying and resolving performance bottlenecks in training pipelines, whether they occur in data loading, computation, or communication between nodes • You have experience working with diverse data types (text, images, video, audio) and can build data pipelines that handle heterogeneous inputs efficiently • Desired experience: You've implemented custom sharding techniques (tensor/pipeline/data parallelism). • You have experience optimizing data pipelines for multimodal datasets with sophisticated preprocessing requirements. • You've built fault-tolerant checkpointing systems that can handle complex model states while minimizing training interruptions. • You've contributed to open-source training infrastructure projects or frameworks. • You've designed training infrastructure that works efficiently for either specialized models or large multimodal systems.

🏖️ Benefícios

• U.S. EQUAL EMPLOYMENT OPPORTUNITY INFORMATION • Liquid AI provides equal employment opportunities without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, or disability. • Completion is voluntary and will not subject you to adverse treatment. • Information obtained will be retained in a confidential file and separate from personnel records.