Video Data Annotator
People Prime Worldwide · India
- Hybrid
- Contract
- $50,000 / year
- India
Job highlights
- Annotate video clips by analyzing visual content.
- Provide evidence-based answers for video analysis.
- Identify and select visual evidence accurately.
- Ensure high consistency and accuracy in tasks.
- Work remotely with contract to hire.
About the role
About Client:
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,” 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:
Job Title: Video Data Annotator
Location: Pan India
Experience: 3+ yrs
Employment Type: Contract to hire
Work Mode: Remote
Notice Period: Immediate joiners
Roles & 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 the 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 Data Annotation
- AI/ML Data
- Computer Vision
- Data Labeling
- Content Moderation
- Quality Assurance
- Visual Interpretation
- Attention to Detail
- Critical Thinking
- Remote Work
Skills & topics
- Video Data Annotator
- Data Annotation
- AI Data
- Computer Vision
- Data Labeling
- Content Moderation
- Quality Assurance
- Remote
- Pan India
- Contract to Hire
How to get hired
- Tailor your resume: Highlight your experience in data annotation, computer vision, or QA roles, emphasizing attention to detail and analytical skills.
- Showcase relevant skills: In your application, detail your ability to follow strict guidelines, maintain consistency, and provide evidence-based analysis for video content.
- Prepare for the interview: Be ready to discuss your experience with data annotation, your understanding of AI/ML workflows, and how you ensure accuracy in repetitive tasks.
- Demonstrate remote work capability: Emphasize your self-discipline, focus, and proactive quality-checking mindset, crucial for remote Video Data Annotator roles.
Technical preparation
Practice analyzing video frames for details.,Study annotation guidelines carefully.,Understand concepts of visual evidence.,Develop logical reasoning skills.
Behavioral questions
Describe a time you handled repetitive tasks.,How do you ensure accuracy in your work?,How do you deal with ambiguity in data?,What motivates you to maintain quality?
Frequently asked questions
- What is the primary responsibility of a Video Data Annotator at People Prime Worldwide?
- As a Video Data Annotator for People Prime Worldwide, your primary responsibility is to review first-person video clips, analyze visual content at specific timestamps, and provide accurate, evidence-based answers grounded in visible information. This involves identifying visual evidence and determining question validity.
- Is this a remote position at People Prime Worldwide?
- Yes, this Video Data Annotator position is a remote role, allowing you to work from anywhere in Pan India. The company, People Prime Worldwide, focuses on connecting companies with remote talent.
- What kind of experience is preferred for the Video Data Annotator role?
- Preferred backgrounds for the Video Data Annotator role include experience in data annotation, data labeling, content moderation, exposure to image/video annotation or computer vision projects, and a background in QA or analytical roles. Familiarity with AI/ML data workflows is also a plus.
- What are the core skills required for a Video Data Annotator at People Prime Worldwide?
- Core skills for a Video Data Annotator include strong attention to detail, excellent observational and visual interpretation skills, clear written communication, strong reading comprehension, critical thinking, and the ability to remain objective and avoid assumptions. High focus and consistency are also key.
- What is the employment type for the Video Data Annotator position?
- The employment type for the Video Data Annotator position at People Prime Worldwide is 'Contract to hire,' meaning you will initially be on a contract basis with the potential for conversion to a permanent role.
- How important is attention to detail for a Video Data Annotator?
- Attention to detail is critically important for a Video Data Annotator. The role requires spotting subtle visual differences, ensuring high consistency and accuracy, and adhering strictly to project guidelines and quality standards. Your ability to remain objective and avoid assumptions is directly tied to your attention to detail.
- What does it mean to 'provide evidence-based answers grounded in visible information' as a Video Data Annotator?
- Providing 'evidence-based answers grounded in visible information' means that your responses must be directly supported by what can be seen in the video at the specified timestamp. You cannot use future frames or external knowledge, ensuring objectivity and accuracy in your annotation.