Member of Technical Staff - Machine Learning Engineer, Training InfrastructureJoin to apply for the Member of Technical Staff - Machine Learning Engineer, Training Infrastructure role at Liquid AIMember of Technical Staff - Machine Learning Engineer, Training Infrastructure1 month ago Be among the first 25 applicantsJoin to apply for the Member of Technical Staff - Machine Learning Engineer, Training Infrastructure role at Liquid AILiquid AI, an MIT spin-off, is a foundation model company headquartered in Boston, Massachusetts. Our mission is to build capable and efficient general-purpose AI systems at every scale.Our goal at Liquid is to build the most capable AI systems to solve problems at every scale, such that users can build, access, and control their AI solutions. This is to ensure that AI will get meaningfully, reliably and efficiently integrated at all enterprises. Long term, Liquid will create and deploy frontier-AI-powered solutions that are available to everyone.What This Role IsWe're looking for a Training Infrastructure Engineer to design, build, and optimize the distributed systems that power our Liquid Foundation Models (LFMs). This is a highly technical role focused on creating the scalable infrastructure that enables efficient training of models across the spectrum—from compact specialized models to massive multimodal systems—while maximizing hardware utilization and minimizing training time.You're A Great Fit IfYou have extensive experience building distributed training infrastructure for language and multimodal models, with hands-on expertise in frameworks like PyTorch Distributed, DeepSpeed, or Megatron-LMYou're passionate about solving complex systems challenges in large-scale model training—from efficient multimodal data loading to sophisticated sharding strategies to robust checkpointing mechanismsYou have a deep understanding of hardware accelerators and networking topologies, with the ability to optimize communication patterns for different parallelism strategiesYou're skilled at identifying and resolving performance bottlenecks in training pipelines, whether they occur in data loading, computation, or communication between nodesYou have experience working with diverse data types (text, images, video, audio) and can build data pipelines that handle heterogeneous inputs efficientlyWhat Sets You ApartYou've implemented custom sharding techniques (tensor/pipeline/data parallelism) to scale training across distributed GPU clusters of varying sizesYou have experience optimizing data pipelines for multimodal datasets with sophisticated preprocessing requirementsYou've built fault-tolerant checkpointing systems that can handle complex model states while minimizing training interruptionsYou've contributed to open-source training infrastructure projects or frameworksYou've designed training infrastructure that works efficiently for both parameter-efficient specialized models and massive multimodal systemsWhat You'll Actually DoDesign and implement high-performance, scalable training infrastructure that efficiently utilizes our GPU clusters for both specialized and large-scale multimodal modelsBuild robust data loading systems that eliminate I/O bottlenecks and enable training on diverse multimodal datasetsDevelop sophisticated checkpointing mechanisms that balance memory constraints with recovery needs across different model scalesOptimize communication patterns between nodes to minimize the overhead of distributed training for long-running experimentsCollaborate with ML engineers to implement new model architectures and training algorithms at scaleCreate monitoring and debugging tools to ensure training stability and resource efficiency across our infrastructureWhat You'll GainThe opportunity to solve some of the hardest systems challenges in AI, working at the intersection of distributed systems and cutting-edge multimodal machine learningExperience building infrastructure that powers the next generation of foundation models across the full spectrum of model scalesThe satisfaction of seeing your work directly enable breakthroughs in model capabilities and performanceSeniority levelSeniority levelNot ApplicableEmployment typeEmployment typeFull-timeJob functionJob functionEngineering and Information TechnologyIndustriesSoftware DevelopmentReferrals increase your chances of interviewing at Liquid AI by 2xGet notified about new Member of Technical Staff jobs in San Francisco, CA.Berkeley, CA $60,000.00-$240,000.00 1 year agoMember of Technical Staff - Computational BiologistMember of Technical Staff, DevSecOps / InfrastructureAlameda, CA $96,000.00-$137,500.00 2 days agoSan Francisco, CA $136,947.00-$239,699.00 5 months agoSenior Principal Software Engineer - AI Platform InnovationRedwood City, CA $96,800.00-$251,600.00 2 days agoAssociate Director of Counseling & Psychological Services - (Administrator II) - Counseling and Psychological ServicesSan Francisco, CA $10,000.00-$120,000.00 8 months agoProject Archaeologist/ Cultural Resources SpecialistOakland, CA $140,000.00-$220,000.00 3 days agoSan Francisco, CA $141,800.00-$221,600.00 2 days agoSan Mateo, CA $141,800.00-$221,600.00 2 days agoSan Francisco, CA $116,000.00-$200,100.00 3 days agoSan Mateo, CA $90,000.00-$140,000.00 1 day agoSan Francisco, CA $150,000.00-$230,000.00 3 weeks agoMember of Technical Staff (Senior/Staff)San Francisco, CA $145,000.00-$220,000.00 4 months agoMember of Technical Staff - Compute PlatformMember of Technical Staff - General InterestQuantum Engineer - Member of Technical StaffSan Francisco, CA $120,000.00-$180,000.00 2 months agoRedwood City, CA $79,800.00-$178,100.00 3 days agoSan Francisco, CA $150,000.00-$225,000.00 4 days agoMember of Technical Staff, Founding Design EngineerSan Francisco, CA $130,000.00-$200,000.00 6 months agoMember of Technical Staff, Founding Frontend EngineerSan Francisco, CA $130,000.00-$200,000.00 5 months agoMember of Technical Staff, Founding Backend EngineerSan Francisco, CA $150,000.00-$200,000.00 6 months agoWe’re unlocking community knowledge in a new way. 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