Research Engineer at Liquid Labs designing novel AI architectures and implementing training methods with a focus on adaptive intelligence. Joining a high-context team with a commitment to open research.
Responsibilities
Join a small, high-context team exploring the limits of adaptive intelligence
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
Requirements
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
Benefits
Open Science and Impact
Commitment to transparent, reproducible, open research
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