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Research Engineer at Liquid Labs | San Francisco

liquid-aiSan Francisco
Remote Full-time

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Experience Level

Experience

Qualifications

Ideal Candidate:Proficient in Python and frameworks such as PyTorch, JAX, or TensorFlow. Experience in machine learning research or developing production-grade ML systems. Ability to rapidly transition from theoretical concepts to prototype implementations, driven by curiosity and precision. Strong focus on efficiency, scalability, and elegant system design as fundamental scientific principles. Appreciate working in small, technically adept teams where your contributions yield immediate and measurable impacts. A proven publication record in top-tier conferences (NeurIPS, ICML, ICLR, CVPR, ACL, or similar), showcasing original contributions and research integrity.

About the job

About Liquid Labs

At Liquid AI, research has always been at the forefront of our mission. Liquid Labs serves as a dedicated internal research accelerator, facilitating groundbreaking advancements in the development of intelligent, personalized, and adaptive machines.

Our roots extend back to MIT CSAIL, where pioneering work on Liquid Neural Networks established a new category of efficient sequence-processing architectures. This research laid the groundwork for our Liquid Foundation Models (LFMs), which are scalable, multimodal models designed for real-world applications in resource-constrained settings.

In Liquid Labs, we continue this legacy by advancing the realm of efficient, adaptive intelligence through both fundamental research and practical engineering efforts.

We collaborate closely with Liquid’s core foundation model and systems teams to turn theoretical concepts into deployable capabilities, setting the stage for a new era of powerful and efficient intelligent systems.

About The Role:

As a Research Engineer at Liquid Labs, you will be part of a dynamic, high-impact team pushing the boundaries of adaptive intelligence. You will be responsible for designing and implementing innovative architectures, training methodologies, and inference strategies to expand the potential of efficient AI.

Your work will blend research and engineering, as you translate scientific concepts into functional systems, publish findings that advance the field, and deploy solutions that redefine what is achievable.

While we prefer candidates from San Francisco and Boston, we welcome applications from other locations within the United States.

About liquid-ai

Liquid AI is dedicated to pioneering research in adaptive intelligence. With a foundation rooted in MIT CSAIL, we are committed to developing innovative solutions that enhance the capabilities of machines, focusing on efficient and scalable artificial intelligence for real-world applications.

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