4 months ago

Member of Technical Staff - Post Training, Applied (Vision)

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 2 hours agoStatus: Live

Job Summary

A hands-on ML engineering role owning end-to-end post-training for vision-language models (VLMs) in production. You’ll translate customer requirements into multimodal post-training specs, manage data generation and evaluation pipelines, and run fine-tuning/RL workflows, shaping how Liquid AI's multimodal stack deploys to enterprise clients.

Location: San Francisco, Boston

Workplace: Hybrid

Employment Type: Full time · Permanent

Job Function: Education & Training

Key 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.

Pay and Benefits

Perks:Health Insurance401kPaid LeaveEquity

Key Requirements

•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/or 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.
•Experience with visual grounding, document understanding, OCR, or video understanding tasks.

Experience:MultimodalVision-language modelsArtificial intelligence

Skills:CommunicationProblem-solvingOwnershipTeamwork

Tech Stack:Vision-language modelsSFTReinforcement learningOCRImage encodersMultimodal pipelines

Company Brief

Liquid AI

Industry: AI & Machine Learning

Website

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Liquid AI

4 months ago

Member of Technical Staff - Post Training, Applied (Vision)

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 2 hours agoStatus: Live

Job Summary

Location: San Francisco, Boston

Workplace: Hybrid

Employment Type: Full time · Permanent

Job Function: Education & Training

Key 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.

Pay and Benefits

Perks:Health Insurance401kPaid LeaveEquity

Key Requirements

•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/or 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.
•Experience with visual grounding, document understanding, OCR, or video understanding tasks.

Experience:MultimodalVision-language modelsArtificial intelligence

Skills:CommunicationProblem-solvingOwnershipTeamwork

Tech Stack:Vision-language modelsSFTReinforcement learningOCRImage encodersMultimodal pipelines

Company Brief

Liquid AI

Industry: AI & Machine Learning

Website