MIT · AI
Role: Member of Technical Staff - Research Engineer, Omni
Team: Omni (Multimodal), Research & Engineering
Location: Boston
Location Type: Hybrid
Employment Type: Full-time
ABOUT LIQUID AI
Spun out of MIT CSAIL, we build general-purpose AI systems that run efficiently across deployment targets, from data center accelerators to on-device hardware, ensuring low latency, minimal memory usage, privacy, and reliability. We partner with enterprises across consumer electronics, automotive, life sciences, and financial services. We are scaling rapidly and need exceptional people to help us get there.
THE OPPORTUNITY
Omni is where Liquid's vision and audio work converges into a single multimodal model, and the next directions, multimodal MoE and token-efficient encoders, are open problems. This is an end-to-end model training role: you will run open research, data, pre- and post-training, evals, and the inference and deployment path for Omni, working directly with the Omni lead and the vision and audio teams, with our Chief Science Officer close to the research. The team is small and has just shipped a release, so there is no layer between you and the model, and the training infrastructure is being consolidated now rather than inherited.
We are open on level: experienced engineers and strong early-career candidates are both considered.
WHAT WE'RE LOOKING FOR
We need someone who
- Owns a task through to done: Takes a loosely defined problem, decides what good looks like, and finishes it well without being chased.
- Research curiosity: Goes deep on why a method