Member of Technical Staff - ML Research Engineer; Multi-Modal - Vision

Work With Us

At Liquid, we're not just building AI models-we're redefining the architecture of intelligence itself. Spun out of MIT, our mission is to build efficient AI systems at every scale. Our Liquid Foundation Models (LFMs) operate where others can't : on-device, at the edge, under real-time constraints. We're not iterating on old ideas-we're architecting what comes next.

We believe great talent powers great technology. The Liquid team is a community of world-class engineers, researchers, and builders creating the next generation of AI. Whether you're helping shape model architectures, scaling our dev platforms, or enabling enterprise deployments-your work will directly shape the frontier of intelligent systems.

This Role Is For You If :

• You have experience with machine learning at scale
• You're proficient in PyTorch, and familiar with distributed training frameworks like DeepSpeed, FSDP, or Megatron-LM
• You've worked with multimodal data (e.g., image-text, video, visual documents, audio)
• You've contributed to research papers, open-source projects, or production-grade multimodal model systems
• You understand how data quality, augmentations, and preprocessing pipelines can significantly impact model performance-and you've built tooling to support that
• You enjoy working in interdisciplinary teams across research, systems, and infrastructure, and can translate ideas into high-impact implementations

Desired Experience :

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About Liquid AI

Spun out of MIT CSAIL, we're a foundation model company headquartered in Boston. Our mission is to build capable and efficient general-purpose AI systems at every scale-from phones and vehicles to enterprise servers and embedded chips. Our models are designed to run where others stall : on CPUs, with low latency, minimal memory, and maximum reliability. We're already partnering with global enterprises across consumer electronics, automotive, life sciences, and financial services. And we're just getting started.