Robotics Annotation Engineer

RemoExperts; España; À distance; EUR 35 000 - 55 000; Plein temps

Résumé du poste

Rex.zone in Spain is seeking a Robotics Annotation Engineer for fully remote work. You will label complex robotics datasets with 2D/3D annotations, including 3D bounding boxes and point clouds, to support AI model training and evaluation.

You will ensure high data quality, follow strict annotation guidelines, and collaborate with AI/ML engineers to improve model performance for autonomous systems across robotics and drone applications.

Qualifications

• Experience with spatial data labeling and QA evaluation.
• Proficiency in computer vision annotation for robotics and autonomous systems.

Responsabilités

• Focus on training data quality and QA evaluation for AI training pipelines.
• Perform complex computer vision annotation (2D/3D) including tracking and sensor fusion labeling.
• Collaborate with AI/ML engineers to refine RLHF protocols and ensure adherence to annotation guidelines.

Connaissances

3D bounding boxes

2D/3D object tracking

Point cloud labeling

RLHF protocols

Outils

Annotation tools

Spatial data tooling

Description du poste

Join Rex.zone to shape the future of autonomous systems. We are hiring remote data labeling experts for robotics annotation jobs in Spain, focusing on computer vision annotation, sensor fusion, and training data quality for AI models.

Robotics Annotation Engineer

Discover premier robotics annotation jobs in Spain through Rex.zone. As a data annotation specialist, you will directly impact AI training pipelines by providing high-quality computer vision annotation and sensor fusion data labeling. This full-time remote role requires deep expertise in 3D bounding boxes, semantic segmentation, and annotation guidelines compliance. Your work ensures model performance improvement for autonomous vehicles, industrial robots, and drone navigation systems. Join leading AI labs and tech startups in building the next generation of embodied AI.

Key Responsibilities In AI Training Pipelines

Your primary focus will be on training data quality and rigorous QA evaluation. Daily tasks involve complex computer vision annotation, including 2D/3D object tracking, point cloud labeling, and kinematic behavior mapping. You will collaborate with AI/ML engineers to refine RLHF (Reinforcement Learning from Human Feedback) protocols for robotic decision-making. Ensuring strict annotation guidelines compliance is critical for large language model evaluation and multimodal AI systems. You will also participate in prompt evaluation and named entity recognition tasks tailored for robotics command interfaces.

Qualifications For Remote Annotation Experts

Ideal candidates for these freelance and full-time remote roles possess a strong background in spatial data labeling and QA evaluation. You must demonstrate proficiency with industry-standard annotation tools and have a proven track record of model performance improvement through precise data curation. Experience with content safety labeling and LLM training pipelines is highly valued. Whether you are an entry-level annotator or a senior data labeling expert, Rex.zone offers a dynamic platform to advance your career in the rapidly growing field of AI/ML and robotics.

Frequently Asked Questions About Robotics Annotation Jobs

What does a robotics data annotation specialist do?

A robotics data annotation specialist labels complex datasets—such as point clouds, video feeds, and sensor fusion logs—to train machine learning models. This computer vision annotation is essential for teaching robots how to navigate, recognize objects, and interact safely with their environments.

Are these robotics annotation jobs in Spain fully remote?

Yes, the roles listed on Rex.zone are fully remote. We offer flexible contract, freelance, and full-time opportunities that allow you to work from anywhere in Spain while collaborating with global AI labs, BPOs, and tech startups.

How does RLHF apply to robotics data labeling?

RLHF (Reinforcement Learning from Human Feedback) is used to fine-tune robotic behaviors and command-response systems. By providing human QA evaluation and prompt evaluation on robotic actions, annotators help improve the safety, accuracy, and alignment of the AI/ML models powering autonomous systems.