Member of Technical Staff, Video Data, Model Evaluation

Cantina

. Define quality standards for video generation across aesthetics, realism, composition, motion, temporal consistency, instruction following, subject consistency, editing preservation, and text rendering.

Posted 10/27/2026full-timeSingapore • SingaporeLeadWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in data strategy and dataset development for generative media, with a strong focus on annotation, quality control, and model evaluation. Capable of translating subjective quality standards into measurable evaluation frameworks and managing large-scale data projects.

Highest-signal resume keywords

Data StrategyDataset DevelopmentModel EvaluationAnnotation GuidelinesGenerative Media Tasks

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Quality ControlAnnotationCaptioning StandardsEvaluation FrameworksVisual JudgmentData Production ManagementQuality ThresholdsFailure AttributionTraining Data ProjectsSynthetic Data Generation

Soft Skills

CollaborationCommunication

Tools & Technologies

PythonSQLVision-Language ModelsAutomated CaptioningWorkflow Automation Tools

Industry Keywords

Generative Image ModelsVideo GenerationMultimodal ModelsInstruction-Based EditingData Initiatives

Tech Stack

Tools & technologies

PythonSQL

About the role

Key responsibilities & impact

Define quality standards for video generation across aesthetics, realism, composition, motion, temporal consistency, instruction following, subject consistency, editing preservation, and text rendering.
Evaluate model iterations, analyze failure patterns, and translate findings into actionable data, training, and prompting strategies.
Own end-to-end training data projects, including sourcing, construction, annotation, captioning, quality control, and delivery.
Develop labeling systems that support dataset segmentation, coverage analysis, quality filtering, training-data mixtures, and model performance attribution.
Design annotation and captioning standards for video generation, editing, and multi-reference tasks.
Create and evaluate synthetic-data workflows based on their stability, usability, quality, and training value.
Develop automated annotation and filtering workflows using vision-language models, system prompts, and quality-scoring models.
Build structured model evaluation processes covering test-set design, evaluation criteria, failure attribution, and reporting.
Establish feedback loops connecting model evaluation and negative-case analysis with data strategy and model iteration.
Train and calibrate annotation teams and external data partners, conduct quality audits, and improve delivery standards.
Partner with research, engineering, product, and creative teams to execute data initiatives and identify future model capabilities.

Requirements

What you’ll need

Hands-on experience in data strategy, dataset development, annotation, or model evaluation for generative image, video, or multimodal models.
Experience supporting model development across continued training, supervised fine-tuning, post-training, or evaluation.
Strong understanding of generative media tasks, including image and video generation, multimodal generation, and instruction-based editing.
Experience developing labeling taxonomies, annotation guidelines, captioning standards, quality thresholds, and evaluation frameworks.
Strong visual judgment and the ability to translate subjective quality expectations into measurable data and evaluation standards.
Experience managing large-scale data-production or annotation projects and collaborating with research, engineering, creative, and external partner teams.
Familiarity with automated captioning, synthetic-data generation, vision-language models, prompt design, Python, SQL, or other data and workflow automation tools is a plus.

Benefits

Comp & perks

Competitive salary and generous company equity
Personal time off and paid holidays
Health insurance
Global travel insurance: Covers you when traveling internationally
Monthly spending stipend: $500 (~S$635)
Equipment: All equipment needed for your home office