Senior Vision-Language Model Engineer (VLM Post-Training) - Equity + Unlimited PTO

Liquid AI; United States; Remote; USD 180,000 - 260,000; Full time

Benefits offered by this job

Equity

Health premiums

401k matching

Unlimited PTO

Refill Days

Job summary

Liquid AI is seeking a hands-on researcher to own enterprise VLM post-training engagements, translating customer needs into concrete multimodal pipelines and workflows. You will design data generation, curation, and evaluation processes, and run fine-tuning and RL workflows to optimize model performance in production environments.

This role emphasizes practical impact over theoretical work, with responsibilities spanning end-to-end delivery, alignment with customers, and contributing to Liquid’s

Qualifications

• Hands-on experience with data generation and evaluation for VLM or multimodal post-training.
• Experience training or fine-tuning vision-language models using SFT, preference alignment, and RL.
• Strong intuition for visual data quality, annotation design, and multimodal evaluation.
• Familiarity with vision encoders, image-text architectures, and how visual representations interact with language model backbones.

Responsibilities

• Act as the technical owner for enterprise customer VLM post-training engagements.
• Translate customer requirements into concrete multimodal post-training specifications and workflows.
• Design and execute visual data generation, filtering, and quality assessment processes, including image-text pair curation, annotation pipelines, and synthetic data generation for visual tasks.
• Run supervised fine-tuning, preference alignment, and reinforcement learning workflows for vision-language models.
• Design task-specific evaluations for visual understanding, grounding, OCR, document parsing, and other multimodal capabilities. Interpret results and feed learnings back into core post-training pipelines.

Skills

VLM post-training

Multimodal data generation

Model evaluation

SFT (supervised fine-tuning)

Reinforcement learning

Tools

Vision encoders

Image-text architectures

Job description

Liquid AI is seeking a hands-on researcher to own enterprise VLM post-training engagements, translating customer needs into concrete multimodal pipelines and workflows. You will design data generation, curation, and evaluation processes, and run fine-tuning and RL workflows to optimize model performance in production environments.

This role emphasizes practical impact over theoretical work, with responsibilities spanning end-to-end delivery, alignment with customers, and contributing to Liquid’s