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Liquid Labs - Research Engineer

Liquid AI· Liquid Labs
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Hybrid (Boston)Full-timePosted 10mo ago

About the role

Research Engineer at Liquid Labs focused on designing and implementing novel architectures, training methods, and inference strategies to advance efficient, adaptive AI. Hybrid work model with preferred locations in Boston or San Francisco, open to other US locations.

Responsibilities

  • - Design and implement novel architectures, training methods, and inference strategies to redefine what efficient AI can do
  • - Operate at the intersection of research and engineering — translating scientific ideas into working systems
  • - Publish where it drives the field forward, and deploy where it changes what’s possible
  • - Collaborate with Liquid’s core foundation model and systems teams to translate theory into deployed capability

Qualifications

  • - Proficiency in Python and frameworks such as PyTorch, JAX, or TensorFlow
  • - Experience in machine learning research or production-grade ML systems
  • - Ability to move quickly from paper to prototype with rigorous, precise work
  • - Commitment to efficiency, scalability, and elegant system design
  • - Experience in small, deep-technical teams with measurable impact
  • - Track record of publication in tier-1 venues (NeurIPS, ICML, ICLR, CVPR, ACL, or equivalent) demonstrating original contribution and research rigor

Skills

Required:PythonPyTorch, JAX, or TensorFlowMachine learning researchSystem design and efficiency
Last updated Jul 15, 2026. Interested? Apply on the company site.
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About Liquid AI

Build efficient general-purpose AI at every scale.

We build efficient general-purpose AI at every scale. Liquid Foundation Models (LFMs) are a new generation of generative AI models that achieve state-of-the-art performance at every scale, while maintaining a smaller memory footprint and more efficient inference.

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