Liquid Labs - Research Engineer

Liquid AI; Boston (MA); On-site; USD 120,000 - 180,000; Full time

Job summary

Liquid Labs is seeking a Research Engineer to push the boundaries of adaptive intelligence. You will design and implement novel architectures, training methods, and inference strategies that fuse research with practical engineering.

Join a small, high-context team at the intersection of theory and production, translating ideas into deployed systems and publishing results that advance the field. Boston or SF preferred, with openness to other US locations.

Qualifications

• Proficient in Python with ML frameworks (PyTorch/JAX/TF).
• Experience in ML research or production-grade ML systems.
• Move quickly from paper to prototype with rigor and precision.
• Care about efficiency, scalability, and elegant system design.
• Value small, deeply technical teams with immediate impact.
• Track record of publication in tier-1 venues (NeurIPS/ICML/ICLR/CVPR/ACL) or equivalent.

Skills

Python

ML frameworks

ML research

Prototype development

System design

Publications

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.

About 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.