Digital Twin & Synthetic Reality Expert(AI Community)

• 3D Point-Cloud Annotation: Working with LiDAR and depth data to identify objects in a 3D space, ensuring the AI understands volume and distance, not just pixels.
• Physics-Consistency Auditing: Evaluating synthetic data (AI-generated environments) to ensure that gravity, lighting, and collisions behave as they do in the real world.
• Spatial Semantic Labeling: Annotating "Digital Twins" of factories, hospitals, or cities to teach AI the function of complex machinery and infrastructure.
• Synthetic-to-Real (Sim2Real) Validation: Comparing AI performance in a simulation versus the real world to identify "reality gaps" and correcting the training data accordingly.

Qualification path

• Education: Minimum of a Bachelor’s Degree in Cybersecurity, Criminal Justice, Forensic Science, or Information Security.
• Native Language: Native-level proficiency in your primary language is mandatory to identify localized document types and regional identity nuances.
• English Proficiency: Minimum B1 (Intermediate) level English.
• Analytical Eye: Exceptional attention to detail, specifically in identifying pixel-level anomalies in digital images.

In order to be hired into our community, you’ll go through a subject-specific qualification exam that will determine your suitability for the position and complete ID verification.