Video Annotator

About Company

Our client is a Palo Alto-based AI infrastructure and talent platform founded in 2018. It helps companies connect with remote software developers using AI-powered vetting and matching technology. Originally branded as the “Intelligent Talent Cloud,” it enabled companies to “spin up their engineering dream team in the cloud” by sourcing and managing vetted global talent. In recent years, they have evolved to support AI infrastructure and AGI workflows, offering services in model training, fine-tuning, and deployment—powered by their internal AI platform, ALAN, and backed by a vast talent network. They reported $300 million in revenue and reached profitability. Their growth is driven by demand for annotated training data from AI labs, including major clients like OpenAI, Google, Anthropic, and Meta.

Job Description

The Video Annotator will review first-person video clips and analyze visual content at specific timestamps, providing accurate, concise, and evidence-based answers grounded in visible information. This role involves identifying and selecting the exact visual evidence supporting each answer and determining whether a question is valid or unanswerable based on the available video content. The annotator must ensure no use of future frames or external assumptions when answering questions and maintain high consistency and accuracy across large volumes of tasks. Adherence to project guidelines, formatting, and quality standards is crucial, along with performing self-reviews to ensure alignment between question, evidence, and answer.

Key Responsibilities

• Review first-person video clips and analyze visual content at specific timestamps.
• Provide accurate, concise, and evidence-based answers grounded in visible information.
• Identify and select the exact visual evidence supporting each answer.
• Determine whether a question is valid or unanswerable based on available video content.
• Ensure no use of future frames or external assumptions when answering questions.
• Maintain high consistency and accuracy across large volumes of tasks.
• Adhere strictly to project guidelines, formatting, and quality standards.
• Perform self-review to ensure alignment between question, evidence, and answer.

Required Skills and Qualifications

Core Skills

• Strong attention to detail and ability to spot subtle visual differences.
• Excellent observational and visual interpretation skills.
• Clear and concise written communication.
• Strong reading comprehension and understanding of nuanced questions.
• Critical thinking and logical reasoning (sequence, counting, spatial awareness).
• Ability to remain objective and avoid assumptions beyond visible data.

Behavioral Traits

• High level of focus and consistency in repetitive, detail-heavy tasks.
• Strong ownership and accountability for quality of work.
• Ability to follow strict guidelines with high precision.
• Self-driven with a proactive quality-check mindset.

Preferred Backgrounds

• Experience in data annotation, data labeling, or content moderation.
• Exposure to image/video annotation or computer vision projects.
• Background in QA, quality assurance, or analytical roles.
• Familiarity with AI/ML data workflows is a plus.

Key skills/competency

• Video Annotation
• Data Labeling
• Content Moderation
• Computer Vision
• AI/ML
• Quality Assurance
• Attention to Detail
• Visual Interpretation
• Critical Thinking
• Communication Skills