Liquid Labs - Research Engineer

Liquid AI; San Francisco (CA); Hybrid; USD 100,000 - 140,000; Full time

Job summary

A pioneering AI research lab is seeking a Research Engineer to push the boundaries of adaptive intelligence. This role involves designing and implementing innovative architectures while translating research ideas into working systems. The ideal candidate is fluent in Python and has experience with frameworks like PyTorch or TensorFlow, along with a strong machine learning research background. With a focus on scalable, efficient AI solutions, this position promises immediate impact in a collaborative small team environment.

Qualifications

• Profound experience in Python and related frameworks.
• Strong background in machine learning research or production.
• Ability to transition from theory to prototype rapidly.

Responsibilities

• Design and implement novel AI architectures and methods.
• Translate scientific concepts into practical systems.
• Publish advancements to drive the field forward.

Skills

Python

PyTorch

JAX

TensorFlow

Machine Learning Research

Production-Grade ML Systems

Job description

About Liquid Labs

Research has been core to Liquid AI from the beginning. Liquid Labs gives that work a formal home; an internal research accelerator driving fundamental breakthroughs in the science of building intelligent, personalized, and adaptive machines. Our origins trace back to MIT CSAIL, where the foundational work on Liquid Neural Networks defined a new class of dynamical, efficient sequence-processing architectures. That research became the basis for Liquid Foundation Models (LFMs). Scalable, multimodal models built for real-world deployment in resource-constrained environments. At Liquid Labs, we extend that lineage - pushing forward the frontier of efficient, adaptive intelligence through both fundamental research and practical engineering. We work hand-in-hand with Liquid’s core foundation model and systems teams to translate theory into deployed capability — defining a new generation of intelligent systems that are both powerful and efficient.

The Role

As a Research Engineer, you’ll join a small, high-context team exploring the limits of adaptive intelligence. You’ll design and implement novel architectures, training methods, and inference strategies to redefine what efficient AI can do. You’ll operate at the intersection of research and engineering — translating scientific ideas into working systems, publishing where it drives the field forward, and deploying where it changes what’s possible. While San Francisco and Boston are preferred, we are open to other locations in the United States.

This Role Is For You If

• Work fluently in Python and frameworks such as PyTorch, JAX, or TensorFlow
• Have experience in machine learning research or production-grade ML systems
• Move fast from paper to prototype — curiosity backed by precision
• Care about efficiency, scalability, and elegant system design as scientific principles
• Value small, deep-technical teams where impact is immediate and measurable
• Have a track record of publication in tier-1 venues (NeurIPS, ICML, ICLR, CVPR, ACL, or equivalent), demonstrating original contribution and research rigor

Open Science and Impact

Liquid Labs reinforces our commitment to transparent, reproducible, open research. We publish through technical reports, architectural deep dives, ablations, and model releases, advancing the broader science of efficient AI while translating breakthroughs into production-ready systems.

Why Liquid Labs

Liquid Labs is for researchers who build. Those who care about lasting impact more than publication count, but who hold themselves to the same scientific standard. We don’t chase benchmarks; we redefine them. We move fast, think deeply, and measure success by the systems that endure.

There is no application deadline. We review candidates on a rolling basis.