Member of Technical Staff - Post Training Applied Vision

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
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.

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Skills

Candidate Availability

Required and preferred rules are kept separate and reflect the wording in the original posting.

About the Role

You will own vision-language model post-training projects from customer requirements through delivery and evaluation. You will curate and generate visual data, run fine-tuning and alignment workflows, evaluate multimodal capabilities, and incorporate learnings into post-training pipelines.

Requirements

  • Experience with data generation and evaluation for vision-language model or multimodal post-training
  • Experience training or fine-tuning vision-language models using SFT, preference alignment, or reinforcement learning
  • Knowledge of visual data quality, annotation design, and multimodal evaluation
  • Familiarity with vision encoders, image-text architectures, and visual representations

Responsibilities

  • Own enterprise vision-language model post-training engagements
  • Translate customer requirements into multimodal post-training specifications and workflows
  • Design visual data generation, filtering, quality assessment, curation, and annotation processes
  • Run supervised fine-tuning, preference-alignment, and reinforcement-learning workflows for vision-language models
  • Design and interpret evaluations for visual understanding, grounding, OCR, and document parsing
  • Feed evaluation learnings into post-training pipelines

Benefits

  • Equity
  • Medical, dental, and vision premiums fully paid for employees and dependents
  • 401(k) matching up to 4% of base pay
  • Unlimited PTO
  • Company-wide Refill Days