Explore full-time remote robotics annotation job opportunities in Austria. Join Rex.zone to power AI/ML training pipelines through computer vision annotation, spatial data labeling, and QA evaluation for next-generation robotic systems.
Title: Remote Robotics Annotation Specialist Date: 21-10-2026 Company: Rex.zone Country: Austria Remote Type: Remote Employment Type: FULL_TIME Experience Level: Mid-Senior Industry: Technology Job Function: Engineering Skills: Robotics Data Annotation, Computer Vision, Spatial Data Labeling, QA Evaluation, 3D Bounding Boxes, RLHF Salary Currency: USD Salary Min: 63360 Salary Max: 126720 Pay Period: YEAR
Are you looking for remote robotics annotation job opportunities in Austria? Rex.zone is hiring dedicated professionals to enhance training data quality for autonomous systems. In this full-time role, you will engage in computer vision annotation, RLHF (Reinforcement Learning from Human Feedback), and QA evaluation. By meticulously labeling spatial data and ensuring strict annotation guidelines compliance, you directly contribute to model performance improvement for cutting-edge AI labs and tech startups. Whether you are an entry-level enthusiast or a senior data labeling expert, your work in LLM training pipelines and robotics data processing will shape the future of automation.
Your daily workflows will involve complex CV annotation tasks, including 2D/3D bounding boxes, semantic segmentation, and LiDAR data labeling. You will perform rigorous QA evaluation to maintain high training data quality. Collaborating with freelance and contract remote workers globally, you will execute prompt evaluation and named entity recognition tailored to robotics AI. Strict annotation guidelines compliance is required to support large language model evaluation and spatial intelligence training.
Ideal candidates for these remote robotics annotation job opportunities in Austria possess a strong background in data labeling and computer vision. You must have experience with AI/ML training pipelines, content safety labeling, and RLHF workflows. Strong attention to detail is essential for model performance improvement. Previous experience working with annotation vendors, BPOs, or AI startups in a remote, full-time, or freelance capacity is highly valued.
A specialist focuses on computer vision annotation, spatial data labeling, and QA evaluation to improve the training data quality for autonomous robots and AI/ML models.
Yes, these are 100% remote roles. You can work from anywhere in Austria, collaborating with our global team of data labeling experts and AI engineers.
Key skills include familiarity with 3D bounding boxes, LiDAR point cloud labeling, semantic segmentation, and strict annotation guidelines compliance to ensure optimal model performance improvement.
While prior experience in RLHF, QA evaluation, or large language model evaluation is a strong plus, we provide comprehensive training for candidates transitioning from other technical or data entry fields.
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