Member of Technical Staff - ML Inference Engineer, Pytorch

Work With Us

At Liquid, we're not just building AI models-we're redefining the architecture of intelligence itself. Spun out of MIT, our mission is to build efficient AI systems at every scale. Our Liquid Foundation Models (LFMs) operate where others can't : on-device, at the edge, under real-time constraints. We're not iterating on old ideas-we're architecting what comes next.

We believe great talent powers great technology. The Liquid team is a community of world-class engineers, researchers, and builders creating the next generation of AI. Whether you're helping shape model architectures, scaling our dev platforms, or enabling enterprise deployments-your work will directly shape the frontier of intelligent systems.

This Role Is For You If :

• You have experience building large-scale production stacks for model serving
• You have a solid understanding of ragged batching, dynamic load balancing, KV-cache management, and other multi-tenant serving techniques
• You have experience with applying quantization strategies (e.g., FP8, INT4) while safeguarding model accuracy
• You have deployed models in both single-GPU and multi-GPU environments and can diagnose performance issues across the stack
Desired Experience :
• PyTorch
• Python
• Model-serving frameworks (e.g. TensorRT, vLLM, SGLang)

What You'll Actually Do :

What You'll Gain :

About Liquid AI

Spun out of MIT CSAIL, we're a foundation model company headquartered in Boston. Our mission is to build capable and efficient general-purpose AI systems at every scale-from phones and vehicles to enterprise servers and embedded chips. Our models are designed to run where others stall : on CPUs, with low latency, minimal memory, and maximum reliability. We're already partnering with global enterprises across consumer electronics, automotive, life sciences, and financial services. And we're just getting started.