Visual Content Quality Analyst

Crossing Hurdles; United States; On-site; USD 55,000 - 75,000; Full time

Job summary

Crossing Hurdles seeks a detail-oriented evaluator to assess visual content for quality, aesthetics, and usefulness in alignment with project guidelines. You will provide objective feedback to support AI training and help improve data pipelines.

The role requires excellent written English, strong analytical thinking, and the ability to flag inconsistencies across diverse datasets. Collaboration with cross-functional teams will refine review criteria and processes.

Qualifications

• Proven experience in visual content evaluation, digital media, or a related field.
• Exceptional written English communication abilities, with high language proficiency.
• Strong analytical skills and keen attention to detail in reviewing visual materials.
• Effective problem-solving skills and the ability to make objective, data-driven decisions.
• Familiarity with digital image formats, quality standards, and basic visual design principles.

Responsibilities

• Evaluate and annotate visual content for quality, aesthetics, and usefulness using project guidelines.
• Provide detailed, objective feedback on image content to support AI training improvements.
• Identify and flag inconsistencies, errors, or suboptimal visuals across diverse datasets.
• Utilize analytical skills to assess image composition, clarity, and adherence to standards.
• Communicate findings clearly in written English with well-reasoned justifications and suggestions.
• Collaborate with cross-functional teams to refine criteria and processes for visual content review.

Skills

Visual content evaluation

Written English communication

Analytical skills

Problem solving

Digital image formats

Job description

Crossing Hurdles seeks a detail-oriented evaluator to assess visual content for quality, aesthetics, and usefulness in alignment with project guidelines. You will provide objective feedback to support AI training and help improve data pipelines.

The role requires excellent written English, strong analytical thinking, and the ability to flag inconsistencies across diverse datasets. Collaboration with cross-functional teams will refine review criteria and processes.