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.