Member of Technical Staff - Post Training Applied Vision
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 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
