Liquid Labs Research Engineer
Liquid AIVisit Liquid AI website
Liquid AI is an efficiency-first foundation-model company building device-native Liquid Foundation Models (LFMs) and tools to customize and deploy them.
Cambridge, Massachusetts, United States
Funding history
About Liquid AI
An MIT CSAIL spinout, Liquid AI develops general-purpose AI models focused on efficient deployment across CPUs, GPUs, NPUs, edge devices, and cloud or on-premises environments.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will design and implement novel AI architectures, training methods, and inference strategies. You will translate scientific ideas into working systems, develop prototypes from research, contribute research publications where appropriate, and deploy technical advances into practical systems.
Requirements
- Python proficiency
- Experience with PyTorch, JAX, or TensorFlow
- Experience in machine learning research or production-grade ML systems
- Experience translating research papers into prototypes
- Knowledge of efficiency, scalability, and system design
- Publication record in tier-one research venues
Responsibilities
- Design and implement novel AI architectures
- Develop training methods and inference strategies
- Translate scientific ideas into working systems
- Build prototypes from research papers
- Publish research findings where appropriate
- Deploy technical advances into practical systems