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← Liquid AI

Member of Technical Staff - Inference Systems

Liquid AI · Boston

CHECKED 23H AGO

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At a glance

Highlights

  • Build benchmarks for inference performance and model quality across hardware.
  • Port models to new platforms and prove outputs are correct end-to-end.
  • Run partner verifications and deliver clear, reproducible findings.

What they offer

  • Equity in a unicorn-stage company
  • 100% medical, dental, and vision premiums for employees and dependents
  • 401(k) matching up to 4% of base pay
  • Unlimited PTO plus company-wide Refill Days

Ideal candidate

A rigorous inference engineer who obsesses over correctness and reproducibility, moves fast with unfamiliar tools, and enjoys validating systems with external partners.

Requirements

  • Hands-on experience with at least one inference framework like llama.cpp, ONNX Runtime, or MLX, including internals and modification
  • Experience designing and building benchmarking pipelines, including methodology, validation, and reproducibility
  • Strong C++ and Python in performance-sensitive contexts
  • Solid understanding of inference fundamentals: quantization, decoding strategies, memory layout, and how they interact

Lab profile

About Liquid AI

MIT CSAIL spinout building efficient general-purpose AI for cloud to edge.

What they build

  • Liquid Foundation Models
  • LFM2.5-Audio

Known for

  • Efficiency-first foundation models
  • Data center to on-device deployment
  • Low latency with minimal memory usage
  • Liquid Neural Networks architecture

Key facts

  • Spun out of MIT CSAIL
More about Liquid AI →
Apply on the lab’s site ↗